CRAN Package Check Results for Package dynamichazard

Last updated on 2019-04-21 13:46:24 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.6.5 487.23 162.46 649.69 ERROR
r-devel-linux-x86_64-debian-gcc 0.6.5 403.70 162.74 566.44 ERROR
r-devel-linux-x86_64-fedora-clang 0.6.5 1062.06 NOTE
r-devel-linux-x86_64-fedora-gcc 0.6.5 966.35 OK
r-devel-windows-ix86+x86_64 0.6.5 1356.00 323.00 1679.00 NOTE
r-patched-linux-x86_64 0.6.5 474.00 199.47 673.47 OK
r-patched-solaris-x86 0.6.5 906.10 ERROR
r-release-linux-x86_64 0.6.5 475.49 187.09 662.58 OK
r-release-windows-ix86+x86_64 0.6.5 1067.00 322.00 1389.00 NOTE
r-release-osx-x86_64 0.6.5 NOTE
r-oldrel-windows-ix86+x86_64 0.6.5 990.00 424.00 1414.00 NOTE
r-oldrel-osx-x86_64 0.6.4 ERROR

Check Details

Version: 0.6.5
Check: tests
Result: ERROR
     Running 'testthat.R' [19s/20s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > # Had the same issue as in this thread: https://github.com/hadley/testthat/issues/86
     > Sys.setenv("R_TESTS" = "")
     >
     > options(deparse.max.lines = 5)
     > suppressWarnings(RNGversion("3.5.0"))
     >
     > testthat::test_check("dynamichazard", reporter = "summary")
     Loading required package: dynamichazard
     Loading required package: survival
     Tracing function "expect_known_value" in package "testthat"
     Tracing function "expect_known_output" in package "testthat"
     Loading required package: DBI
     Running tests for GMA: ..................
     Testing LAPACK wrapper functions: ....1......................................
     Running test_PF: ........................................................................................................................................................................................................SS...SSSSSSSS..S2SS..SSSSSSSSS
     Testing SMA: ...........3.4567........89
     Testing UKF: .........................
     Testing bigglm_wrapper: ..........
     Testing boot: ...Sab..............................................................................................................................................................................................................................................................................................................................................................................................................
    
     == Skipped =====================================================================
     1. PF_smooth gives same results (@test_PF.R#71) - On CRAN
    
     2. Import and export PF cloud from Rcpp gives the same (@test_PF.R#249) - On CRAN
    
     3. PF_EM gives previous results on head neck data set (@test_PF.R#342) - On CRAN
    
     4. PF_EM gives previous results on head neck data set with fixed effects and the logit model (@test_PF.R#409) - On CRAN
    
     5. compute_PF_summary_stats gives previous results (@test_PF.R#434) - On CRAN
    
     6. 'get_cloud_means' and 'get_cloud_quantiles' gives previous results (@test_PF.R#508) - On CRAN
    
     7. 'get_ancestors' yields the correct result (@test_PF.R#558) - On CRAN
    
     8. <U+00B4>est_params_dens<U+00B4> gives the same as a R version (@test_PF.R#580) - On CRAN
    
     9. fixed effect estimation gives the same as an R implementation (@test_PF.R#628) - On CRAN
    
     10. A few iterations with `type = "VAR"' yields the same as before (@test_PF.R#709) - On CRAN
    
     11. PF_EM gives the same with restricted and unrestricted model when we estimate all the parameters (@test_PF.R#778) - On CRAN
    
     12. Using `n_smooth_final` works as expected and yields previous results (@test_PF.R#883) - On CRAN
    
     13. sampling with a t-distribution gives previous results (@test_PF.R#949) - On CRAN
    
     14. 'PF_forward_filter' gives the same as 'PF_EM' when it should (@test_PF.R#987) - On CRAN
    
     15. 'state_fw' gives correct results (@test_PF.R#1116) - !dir.exists("pf-internals")
    
     16. 'state_bw' gives correct results (@test_PF.R#1152) - !dir.exists("pf-internals")
    
     17. 'artificial_prior' gives correct results (@test_PF.R#1187) - !dir.exists("pf-internals")
    
     18. 'observational_cdist' gives correct results (@test_PF.R#1221) - !dir.exists("pf-internals")
    
     19. combining forward and backwards works (@test_PF.R#1266) - !dir.exists("pf-internals")
    
     20. combining prior and backwards works (@test_PF.R#1313) - !dir.exists("pf-internals")
    
     21. mode approximations give expected result (@test_PF.R#1351) - !dir.exists("pf-internals")
    
     22. 'PF_get_score_n_hess' gives the same as an R implementation (@test_PF.R#1493) - On CRAN
    
     23. boot yields previously computed values with pbc (@test_boot_est.R#19) - On CRAN
    
     == Failed ======================================================================
     -- 1. Error: Square triangular inversion works followed by rank one update (@tes
     BLAS/LAPACK routine 'DTRTI2' gave error code -1
     1: square_tri_inv_test(d1) at testthat/test_LAPACK_BLAS.R:98
    
     -- 2. Error: type = 'VAR' works with non-zero mean with a single term and gives
     BLAS/LAPACK routine 'DTRTI2' gave error code -1
     1: suppressWarnings(PF_EM(Surv(start, stop, event) ~ ddFixed(group) + ddFixed_intercept(TRUE),
     head_neck_cancer, Q_0 = 1, Q = 0.2, Fmat = diag(0.01, 1), by = 1, type = "VAR",
     model = "logit", max_T = 30, control = PF_control(N_fw_n_bw = 50, N_smooth = 100,
     N_first = 500, eps = 0.001, method = "AUX_normal_approx_w_cloud_mean", n_max = 2,
     smoother = "Fearnhead_O_N", Q_tilde = diag(0.3^2, 1), n_threads = 1))) at testthat/test_PF.R:851
     2: withCallingHandlers(expr, warning = function(w) invokeRestart("muffleWarning"))
     3: PF_EM(Surv(start, stop, event) ~ ddFixed(group) + ddFixed_intercept(TRUE), head_neck_cancer,
     Q_0 = 1, Q = 0.2, Fmat = diag(0.01, 1), by = 1, type = "VAR", model = "logit",
     max_T = 30, control = PF_control(N_fw_n_bw = 50, N_smooth = 100, N_first = 500,
     eps = 0.001, method = "AUX_normal_approx_w_cloud_mean", n_max = 2, smoother = "Fearnhead_O_N",
     Q_tilde = diag(0.3^2, 1), n_threads = 1))
     4: .PF_EM(trace = trace, seed = seed, fixed_params = fixed_params, type = type, n_fixed_terms_in_state_vec = static_args$n_fixed_terms_in_state_vec,
     X = static_args$X, fixed_terms = static_args$fixed_terms, tstart = static_args$tstart,
     tstop = static_args$tstop, risk_obj = static_args$risk_obj, debug = static_args$debug,
     model = static_args$model, Q = model_args$Q, Q_0 = model_args$Q_0, F. = model_args$F.,
     R = model_args$R, a_0 = model_args$a_0, G = model_args$G, J = model_args$J, K = model_args$K,
     5: eval(fit_call, envir = parent.frame())
     6: eval(fit_call, envir = parent.frame())
     7: PF_smooth(n_fixed_terms_in_state_vec = static_args$n_fixed_terms_in_state_vec, X = static_args$X,
     fixed_terms = static_args$fixed_terms, tstart = static_args$tstart, tstop = static_args$tstop,
     Q_0 = structure(0.2000200020002, .Dim = c(1L, 1L)), Q = structure(0.2, .Dim = c(1L,
     1L)), a_0 = 0, R = model_args$R, risk_obj = static_args$risk_obj, n_max = control$n_max,
     n_threads = control$n_threads, N_fw_n_bw = control$N_fw_n_bw, N_smooth = control$N_smooth,
    
     -- 3. Error: Changing between woodbury and cholesky makes a slight difference wi
     BLAS/LAPACK routine 'DTRTI2' gave error code -1
     1: eval(cl) at testthat/test_SMA.R:77
     2: eval(cl)
     3: ddhazard(Surv(tstart, tstop, death == 2) ~ age + edema + log(albumin) + log(protime) +
     log(bili), pbc2, id = pbc2$id, by = 100, max_T = 3600, control = ctrl, Q_0 = diag(rep(1e+05,
     6)), Q = diag(rep(0.01, 6)))
     4: tryCatch({
     result <- ddhazard_no_validation(a_0 = a_0, Q_0 = Q_0, F. = F., verbose = verbose,
     Q = Q, risk_set = risk_set, X_Y = X_Y, model = model, R = R, L = L, LR = control$LR *
     control$LR_decrease_fac^(k), n_fixed_terms_in_state_vec = ifelse(est_fixed_in_E,
     n_fixed, 0), weights = weights, control)
     5: tryCatchList(expr, classes, parentenv, handlers)
     6: tryCatchOne(expr, names, parentenv, handlers[[1L]])
     7: value[[3L]](cond)
    
     -- 4. Error: Logit model for posterior_approx gives previous found values with w
     BLAS/LAPACK routine 'DTRTI2' gave error code -1
     1: eval(cl) at testthat/test_SMA.R:107
     2: eval(cl)
     3: ddhazard(formula = survival::Surv(start, stop, event) ~ group, data = head_neck_cancer,
     by = 1, control = ddhazard_control(est_Q_0 = F, method = "SMA", save_data = F,
     save_risk_set = F, eps = 0.01), Q_0 = diag(1e+05, 2), Q = diag(0.01, 2),
     max_T = 45, order = 1)
     4: tryCatch({
     result <- ddhazard_no_validation(a_0 = a_0, Q_0 = Q_0, F. = F., verbose = verbose,
     Q = Q, risk_set = risk_set, X_Y = X_Y, model = model, R = R, L = L, LR = control$LR *
     control$LR_decrease_fac^(k), n_fixed_terms_in_state_vec = ifelse(est_fixed_in_E,
     n_fixed, 0), weights = weights, control)
     5: tryCatchList(expr, classes, parentenv, handlers)
     6: tryCatchOne(expr, names, parentenv, handlers[[1L]])
     7: value[[3L]](cond)
    
     -- 5. Error: Chaning the learning changes the result for the posterior approx me
     BLAS/LAPACK routine 'DTRTI2' gave error code -1
     1: eval(cl) at testthat/test_SMA.R:131
     2: eval(cl)
     3: ddhazard(formula = survival::Surv(start, stop, event) ~ group, data = head_neck_cancer,
     by = 1, control = ctrl, Q_0 = diag(1e+05, 2), Q = diag(0.01, 2), max_T = 45,
     order = 1)
     4: tryCatch({
     result <- ddhazard_no_validation(a_0 = a_0, Q_0 = Q_0, F. = F., verbose = verbose,
     Q = Q, risk_set = risk_set, X_Y = X_Y, model = model, R = R, L = L, LR = control$LR *
     control$LR_decrease_fac^(k), n_fixed_terms_in_state_vec = ifelse(est_fixed_in_E,
     n_fixed, 0), weights = weights, control)
     5: tryCatchList(expr, classes, parentenv, handlers)
     6: tryCatchOne(expr, names, parentenv, handlers[[1L]])
     7: value[[3L]](cond)
    
     -- 6. Error: Second order model gives previous found result for posterior approx
     BLAS/LAPACK routine 'DTRTI2' gave error code -1
     1: ddhazard(formula = survival::Surv(start, stop, event) ~ group, data = head_neck_cancer,
     by = 1, control = ddhazard_control(method = "SMA"), Q_0 = diag(1, 4), Q = diag(0.01,
     2), max_T = 30, order = 2) at testthat/test_SMA.R:151
     2: tryCatch({
     result <- ddhazard_no_validation(a_0 = a_0, Q_0 = Q_0, F. = F., verbose = verbose,
     Q = Q, risk_set = risk_set, X_Y = X_Y, model = model, R = R, L = L, LR = control$LR *
     control$LR_decrease_fac^(k), n_fixed_terms_in_state_vec = ifelse(est_fixed_in_E,
     n_fixed, 0), weights = weights, control)
     3: tryCatchList(expr, classes, parentenv, handlers)
     4: tryCatchOne(expr, names, parentenv, handlers[[1L]])
     5: value[[3L]](cond)
    
     -- 7. Error: Posterior gives previous found results with large by length for pbc
     BLAS/LAPACK routine 'DTRTI2' gave error code -1
     1: ddhazard(Surv(tstart, tstop, death == 2) ~ age + edema + log(albumin) + log(protime) +
     log(bili), pbc2, id = pbc2$id, by = 300, max_T = 3600, control = ddhazard_control(method = "SMA"),
     Q_0 = diag(rep(1e+05, 6)), Q = diag(rep(0.001, 6))) at testthat/test_SMA.R:168
     2: tryCatch({
     result <- ddhazard_no_validation(a_0 = a_0, Q_0 = Q_0, F. = F., verbose = verbose,
     Q = Q, risk_set = risk_set, X_Y = X_Y, model = model, R = R, L = L, LR = control$LR *
     control$LR_decrease_fac^(k), n_fixed_terms_in_state_vec = ifelse(est_fixed_in_E,
     n_fixed, 0), weights = weights, control)
     3: tryCatchList(expr, classes, parentenv, handlers)
     4: tryCatchOne(expr, names, parentenv, handlers[[1L]])
     5: value[[3L]](cond)
    
     -- 8. Error: Exponential model for posterior_approx gives previous found values
     BLAS/LAPACK routine 'DTRTI2' gave error code -1
     1: eval(cl) at testthat/test_SMA.R:225
     2: eval(cl)
     3: ddhazard(Surv(tstart, tstop, death == 2) ~ age + edema + log(albumin) + log(protime) +
     log(bili), pbc2, id = pbc2$id, by = 100, max_T = 3600, model = "exp_clip_time_w_jump",
     control = ddhazard_control(method = "SMA", eps = 0.01), Q_0 = diag(rep(1e+05,
     6)), Q = diag(rep(0.001, 6)))
     4: tryCatch({
     result <- ddhazard_no_validation(a_0 = a_0, Q_0 = Q_0, F. = F., verbose = verbose,
     Q = Q, risk_set = risk_set, X_Y = X_Y, model = model, R = R, L = L, LR = control$LR *
     control$LR_decrease_fac^(k), n_fixed_terms_in_state_vec = ifelse(est_fixed_in_E,
     n_fixed, 0), weights = weights, control)
     5: tryCatchList(expr, classes, parentenv, handlers)
     6: tryCatchOne(expr, names, parentenv, handlers[[1L]])
     7: value[[3L]](cond)
    
     -- 9. Error: Exponential model yields the same results for all the method inputs
     BLAS/LAPACK routine 'DTRTI2' gave error code -1
     1: eval(cl) at testthat/test_SMA.R:240
     2: eval(cl)
     3: ddhazard(Surv(tstart, tstop, death == 2) ~ age + edema + log(albumin) + log(protime) +
     log(bili), pbc2, id = pbc2$id, by = 100, max_T = 3600, model = "exp_clip_time_w_jump",
     control = ddhazard_control(method = "SMA", eps = 0.01), Q_0 = diag(rep(1e+05,
     6)), Q = diag(rep(0.001, 6)))
     4: tryCatch({
     result <- ddhazard_no_validation(a_0 = a_0, Q_0 = Q_0, F. = F., verbose = verbose,
     Q = Q, risk_set = risk_set, X_Y = X_Y, model = model, R = R, L = L, LR = control$LR *
     control$LR_decrease_fac^(k), n_fixed_terms_in_state_vec = ifelse(est_fixed_in_E,
     n_fixed, 0), weights = weights, control)
     5: tryCatchList(expr, classes, parentenv, handlers)
     6: tryCatchOne(expr, names, parentenv, handlers[[1L]])
     7: value[[3L]](cond)
    
     -- 10. Error: Boot works with posterior_approx and gives previous found results
     BLAS/LAPACK routine 'DTRTI2' gave error code -1
     1: ddhazard(formula = survival::Surv(start, stop, event) ~ group, data = head_neck_cancer,
     by = 1, control = ddhazard_control(method = "SMA", eps = 0.01), Q_0 = diag(1e+05,
     2), Q = diag(0.01, 2), max_T = 45) at testthat/test_boot_est.R:80
     2: tryCatch({
     result <- ddhazard_no_validation(a_0 = a_0, Q_0 = Q_0, F. = F., verbose = verbose,
     Q = Q, risk_set = risk_set, X_Y = X_Y, model = model, R = R, L = L, LR = control$LR *
     control$LR_decrease_fac^(k), n_fixed_terms_in_state_vec = ifelse(est_fixed_in_E,
     n_fixed, 0), weights = weights, control)
     3: tryCatchList(expr, classes, parentenv, handlers)
     4: tryCatchOne(expr, names, parentenv, handlers[[1L]])
     5: value[[3L]](cond)
     ... and 1 more
    
    
     Maximum number of 10 failures reached, some test results may be missing.
    
     == DONE ========================================================================
     Error: Test failures
     Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.6.5
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building 'Comparing_methods_for_logistic_models.Rmd' using rmarkdown
    This is mgcv 1.8-28. For overview type 'help("mgcv-package")'.
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    Quitting from lines 427-444 (Comparing_methods_for_logistic_models.Rmd)
    Error: processing vignette 'Comparing_methods_for_logistic_models.Rmd' failed with diagnostics:
    BLAS/LAPACK routine 'DTRTI2' gave error code -1
    --- failed re-building 'Comparing_methods_for_logistic_models.Rmd'
    
    --- re-building 'Diagnostics.Rmd' using rmarkdown
    Loading required package: survival
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    --- finished re-building 'Diagnostics.Rmd'
    
    --- re-building 'ddhazard.Rnw' using knitr
    fatal: not a git repository (or any of the parent directories): .git
    Warning in system("git rev-parse --short HEAD", intern = TRUE) :
     running command 'git rev-parse --short HEAD' had status 128
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    a_0 not supplied. IWLS estimates of static glm model is used for random walk models. Otherwise the values are zero
    --- finished re-building 'ddhazard.Rnw'
    
    --- re-building 'Bootstrap_illustration.pdf.asis' using asis
    --- finished re-building 'Bootstrap_illustration.pdf.asis'
    
    --- re-building 'Particle_filtering.pdf.asis' using asis
    --- finished re-building 'Particle_filtering.pdf.asis'
    
    SUMMARY: processing the following file failed:
     'Comparing_methods_for_logistic_models.Rmd'
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.6.5
Check: tests
Result: ERROR
     Running ‘testthat.R’ [47s/77s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > # Had the same issue as in this thread: https://github.com/hadley/testthat/issues/86
     > Sys.setenv("R_TESTS" = "")
     >
     > options(deparse.max.lines = 5)
     > suppressWarnings(RNGversion("3.5.0"))
     >
     > testthat::test_check("dynamichazard", reporter = "summary")
     Loading required package: dynamichazard
     Loading required package: survival
     Tracing function "expect_known_value" in package "testthat"
     Tracing function "expect_known_output" in package "testthat"
     Loading required package: DBI
     Running tests for GMA: ..................
     Testing LAPACK wrapper functions: ....123.......................................
     Running test_PF: ........................................................................................................................................................................................................SS...SSSSSSSS..S..SS..SSSSSSSSS
     Testing SMA: ...........W.4.....WWWWWWW56........W7WW.W.W.
     Testing UKF: .........................
     Testing bigglm_wrapper: ..........
     Testing boot: ...S.8................................................................................................................................................................................................................................................................................................................................................................................................................
     testing cloglog link function: ....S
     Testing cpp sampling functions: ..................................................................................................................................................................................................................................................................................................................................................................................................................S.............................................................S....
     Running test_cpp_utils.R:: .S............
     Testing ddhazard w/ generic things and w/ the the EKF : .....................S................
     Testing design_mat_and_risk_obj: ............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
     Testing fixed_effects_in_E_step: ........9
     Testing test_fixed_effects_in_M_step: ..........S..
     Testing 'get_start_values': ....................
     Running tests for hatvalues: ....
     Testing examples in man files: .......S.S....SSSS........S
     Testing loglike: ........................
     Testing options: .
     Testing parallelglm vs. glm: ................................................S
     Testing plot functions: ......................................
     Testing predict: ...............................................................................SS
     Testing print function: ...SS.....
     Testing residuals functions: ..................................................................................................................................................................................................SS
     Testing shiny app: ..
     Testing static_glm: .............................
     Testing summary function: .................
     Testing test_utils: ............S......................................
     Testing weights in fit: ................
    
     ══ Skipped ═════════════════════════════════════════════════════════════════════
     1. PF_smooth gives same results (@test_PF.R#71) - On CRAN
    
     2. Import and export PF cloud from Rcpp gives the same (@test_PF.R#249) - On CRAN
    
     3. PF_EM gives previous results on head neck data set (@test_PF.R#342) - On CRAN
    
     4. PF_EM gives previous results on head neck data set with fixed effects and the logit model (@test_PF.R#409) - On CRAN
    
     5. compute_PF_summary_stats gives previous results (@test_PF.R#434) - On CRAN
    
     6. 'get_cloud_means' and 'get_cloud_quantiles' gives previous results (@test_PF.R#508) - On CRAN
    
     7. 'get_ancestors' yields the correct result (@test_PF.R#558) - On CRAN
    
     8. ´est_params_dens´ gives the same as a R version (@test_PF.R#580) - On CRAN
    
     9. fixed effect estimation gives the same as an R implementation (@test_PF.R#628) - On CRAN
    
     10. A few iterations with `type = "VAR"' yields the same as before (@test_PF.R#709) - On CRAN
    
     11. PF_EM gives the same with restricted and unrestricted model when we estimate all the parameters (@test_PF.R#778) - On CRAN
    
     12. Using `n_smooth_final` works as expected and yields previous results (@test_PF.R#883) - On CRAN
    
     13. sampling with a t-distribution gives previous results (@test_PF.R#949) - On CRAN
    
     14. 'PF_forward_filter' gives the same as 'PF_EM' when it should (@test_PF.R#987) - On CRAN
    
     15. 'state_fw' gives correct results (@test_PF.R#1116) - !dir.exists("pf-internals")
    
     16. 'state_bw' gives correct results (@test_PF.R#1152) - !dir.exists("pf-internals")
    
     17. 'artificial_prior' gives correct results (@test_PF.R#1187) - !dir.exists("pf-internals")
    
     18. 'observational_cdist' gives correct results (@test_PF.R#1221) - !dir.exists("pf-internals")
    
     19. combining forward and backwards works (@test_PF.R#1266) - !dir.exists("pf-internals")
    
     20. combining prior and backwards works (@test_PF.R#1313) - !dir.exists("pf-internals")
    
     21. mode approximations give expected result (@test_PF.R#1351) - !dir.exists("pf-internals")
    
     22. 'PF_get_score_n_hess' gives the same as an R implementation (@test_PF.R#1493) - On CRAN
    
     23. boot yields previously computed values with pbc (@test_boot_est.R#19) - On CRAN
    
     24. cloglog function gives previous result with simulated data using PF_EM and PF_forward_filter (@test_cloglog.R#56) - On CRAN
    
     25. mvrnorm gives expected sample mean and variance (@test_cpp_sample_funcs.R#50) - On CRAN
    
     26. 'mvtrnorm' yields close to uniform sample (@test_cpp_sample_funcs.R#111) - On CRAN
    
     27. trunc_lp_in_exponential_dist does not truncate when not needed (@test_cpp_utils.R#12) - On CRAN
    
     28. Different non-integer time_scales gives the same result with ddhazard (@test_ddhazard_n_EKF.R#165) - On CRAN
    
     29. posterior_approx gives previous found values with fixed effects in M-step (@test_fixed_effects_in_M_step.R#187) - On CRAN
    
     30. residuals.ddhazard help page examples gives the same results (@test_help_page_examples.R#43) - On CRAN
    
     31. ddhazard_boot help page examples gives the same results (@test_help_page_examples.R#67) - On CRAN
    
     32. PF_EM help page example runs and gives previous computed results (@test_help_page_examples.R#129) - On CRAN
    
     33. Second example on PF help page gives the same result (@test_help_page_examples.R#170) - On CRAN
    
     34. example in 'PF_EM' with gives previous results w/ a few iterations (@test_help_page_examples.R#226) - On CRAN
    
     35. `PF_forward_filter` the results stated in the comments and does not alter the .Random.seed as stated on the help page (@test_help_page_examples.R#357) - On CRAN
    
     36. 'PF_get_score_n_hess' gives previous results (@test_help_page_examples.R#515) - On CRAN
    
     37. glm and parallelglm gives the same (@test_parallelglm.R#80) - On CRAN
    
     38. Terms from predict with exponential outcome are correct (@test_predict.R#413) - On CRAN
    
     39. Different non-integer time_scales gives the same result with predict results (@test_predict.R#474) - On CRAN
    
     40. print.ddhazard_boot gives the expected output (@test_print.R#39) - On CRAN
    
     41. Print function for PF objects gives previous results (@test_print.R#89) - On CRAN
    
     42. Gets previous results with Rossi (@test_residuals.R#209) - On CRAN
    
     43. Get prevoius residuals with whas500 (@test_residuals.R#236) - On CRAN
    
     44. Testing util functions to sim series for tests (@test_test_utils.R#28) - On CRAN
    
     ══ Warnings ════════════════════════════════════════════════════════════════════
     1. Changing between woodbury and cholesky makes a slight difference with PBC (@test_SMA.R#77) - EM algorithm did not converge within the n_max number of iterations
    
     2. Second order model gives previous found result for posterior approx (@test_SMA.R#151) - Q - Q.t() maximal element difference was 2.5353e+30 in iteration 3
    
     3. Second order model gives previous found result for posterior approx (@test_SMA.R#151) - Newton Rapshon in prediction step failed at least once
    
     4. Second order model gives previous found result for posterior approx (@test_SMA.R#151) - Q - Q.t() maximal element difference was 1.56928e+57 in iteration 3
    
     5. Second order model gives previous found result for posterior approx (@test_SMA.R#151) - Q - Q.t() maximal element difference was 1.06338e+37 in iteration 3
    
     6. Second order model gives previous found result for posterior approx (@test_SMA.R#151) - Q - Q.t() maximal element difference was 1.54743e+26 in iteration 3
    
     7. Second order model gives previous found result for posterior approx (@test_SMA.R#151) - Q - Q.t() maximal element difference was 7.20576e+16 in iteration 3
    
     8. Second order model gives previous found result for posterior approx (@test_SMA.R#151) - Q - Q.t() maximal element difference was 1.09951e+12 in iteration 3
    
     9. Exponential model for posterior_approx gives previous found values (@test_SMA.R#225) - EM algorithm did not converge within the n_max number of iterations
    
     10. Exponential model yields the same results for all the method inputs with same seed (@test_SMA.R#240) - EM algorithm did not converge within the n_max number of iterations
    
     11. Exponential model yields the same results for all the method inputs with same seed (@test_SMA.R#245) - EM algorithm did not converge within the n_max number of iterations
    
     12. Exponential model yields the same results for all the method inputs with same seed (@test_SMA.R#245) - EM algorithm did not converge within the n_max number of iterations
    
     13. Exponential model yields the same results for all the method inputs with same seed (@test_SMA.R#245) - EM algorithm did not converge within the n_max number of iterations
    
     ══ Failed ══════════════════════════════════════════════════════════════════════
     ── 1. Failure: Square triangular inversion works followed by rank one update (@t
     solve(d1) not equal to `d2`.
     15/25 mismatches (average diff: 0.703)
     [1] 0.3908 - 2.5586 == -2.168
     [2] 0.0241 - -0.0874 == 0.112
     [3] 0.1255 - -0.3374 == 0.463
     [4] 0.1447 - -0.6215 == 0.766
     [5] 0.2003 - -0.8917 == 1.092
     [7] 0.7054 - 1.4176 == -0.712
     [8] -0.0509 - 0.0749 == -0.126
     [9] -0.1914 - 0.4559 == -0.647
     [10] 0.4207 - -0.7829 == 1.204
     ...
    
     ── 2. Failure: Square triangular inversion works followed by rank one update (@t
     solve(d1) not equal to `d2`.
     55/100 mismatches (average diff: 0.626)
     [1] 0.4262 - 2.3463 == -1.9202
     [2] -0.0499 - 0.3039 == -0.3539
     [3] -0.1709 - 0.8763 == -1.0471
     [4] -0.0169 - -0.0718 == 0.0549
     [5] -0.0783 - 0.3736 == -0.4519
     [6] -0.1376 - 0.5702 == -0.7078
     [7] 0.0589 - -0.0569 == 0.1158
     [8] -0.0461 - 0.1263 == -0.1725
     [9] 0.0481 - -0.2147 == 0.2627
     ...
    
     ── 3. Failure: Square triangular inversion works followed by rank one update (@t
     solve(d1) not equal to `d2`.
     1275/2500 mismatches (average diff: 0.269)
     [1] 0.538126 - 1.85830 == -1.3202
     [2] 0.036212 - -0.14812 == 0.1843
     [3] 0.014338 - -0.05850 == 0.0728
     [4] -0.033743 - 0.12339 == -0.1571
     [5] -0.006282 - 0.02669 == -0.0330
     [6] 0.010689 - -0.00936 == 0.0201
     [7] -0.000124 - 0.03283 == -0.0330
     [8] 0.005670 - -0.00541 == 0.0111
     [9] -0.004830 - -0.01655 == 0.0117
     ...
    
     ── 4. Failure: Changing between woodbury and cholesky makes a slight difference
     f1[c("state_vars", "state_vecs")] not equal to f2[c("state_vars", "state_vecs")].
     Component "state_vars": Mean relative difference: 2.545334
     Component "state_vecs": Mean relative difference: 1.959576
    
     ── 5. Error: Second order model gives previous found result for posterior approx
     Failed to estimate model. The following learning rates was tried: 1, 0.9, 0.81, 0.729, 0.6561, 0.59049, 0.531441, 0.4782969, 0.43046721, 0.387420489. Try decreasing the learning rate or change denom_term
     1: ddhazard(formula = survival::Surv(start, stop, event) ~ group, data = head_neck_cancer,
     by = 1, control = ddhazard_control(method = "SMA"), Q_0 = diag(1, 4), Q = diag(0.01,
     2), max_T = 30, order = 2) at testthat/test_SMA.R:151
     2: stop("Failed to estimate model. The following learning rates was tried: ", paste0(control$LR *
     control$LR_decrease_fac^k_vals, collapse = ", "), ". Try decreasing the learning rate or change denom_term")
    
     ── 6. Failure: Posterior gives previous found results with large by length for p
     `f1` not equal to read_to_test("posterior_approx_logit_pbc_large_by").
     Component "state_vecs": Mean relative difference: 0.7123655
     Component "state_vecs": Mean relative difference: 0.7123655
    
     ── 7. Failure: Exponential model for posterior_approx gives previous found value
     `f1` not equal to read_to_test("posterior_approx_exp_pbc").
     Component "state_vecs": Mean relative difference: 0.9213003
     Component "state_vecs": Mean relative difference: 0.9213003
    
     ── 8. Failure: Boot works with posterior_approx and gives previous found results
     `tmp` not equal to read_to_test("boot_posterior_approx").
     Component "t0": Mean relative difference: 0.2941322
     Component "t": Mean relative difference: 0.3619236
    
     ── 9. Error: posterior_approx gives previous found values with fixed effects in
     Failed to estimate model. The following learning rates was tried: 1, 0.9, 0.81, 0.729, 0.6561, 0.59049, 0.531441, 0.4782969, 0.43046721, 0.387420489. Try decreasing the learning rate or change denom_term
     1: ddhazard(Surv(tstart, tstop, death == 2) ~ ddFixed(age) + ddFixed(edema) + log(albumin) +
     log(protime) + log(bili), pbc2, id = pbc2$id, by = 100, max_T = 3600, control = ddhazard_control(method = "SMA",
     fixed_terms_method = "E_step"), Q_0 = diag(rep(1e+05, 4)), Q = diag(rep(0.01,
     4))) at testthat/test_fixed_effects_in_E_step.R:157
     2: stop("Failed to estimate model. The following learning rates was tried: ", paste0(control$LR *
     control$LR_decrease_fac^k_vals, collapse = ", "), ". Try decreasing the learning rate or change denom_term")
    
     ══ DONE ════════════════════════════════════════════════════════════════════════
     Error: Test failures
     Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.6.5
Check: installed package size
Result: NOTE
     installed size is 32.1Mb
     sub-directories of 1Mb or more:
     data 4.2Mb
     doc 1.6Mb
     libs 25.8Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-windows-ix86+x86_64, r-patched-solaris-x86, r-release-windows-ix86+x86_64, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64

Version: 0.6.5
Check: tests
Result: ERROR
     Running ‘testthat.R’ [84s/118s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > # Had the same issue as in this thread: https://github.com/hadley/testthat/issues/86
     > Sys.setenv("R_TESTS" = "")
     >
     > options(deparse.max.lines = 5)
     > suppressWarnings(RNGversion("3.5.0"))
     >
     > testthat::test_check("dynamichazard", reporter = "summary")
     Loading required package: dynamichazard
     Loading required package: survival
     Tracing function "expect_known_value" in package "testthat"
     Tracing function "expect_known_output" in package "testthat"
     Loading required package: DBI
     Running tests for GMA: ..................
     Testing LAPACK wrapper functions: ..............................................
     Running test_PF: ........................................................................................................................................................................................................SS...SSSSSSSS..S12SS..SSSSSSSSS
     Testing SMA: ................................
     Testing UKF: .........................
     Testing bigglm_wrapper: ..........
     Testing boot: ...S..................................................................................................................................................................................................................................................................................................................................................................................................................
     testing cloglog link function: ....S
     Testing cpp sampling functions: ..................................................................................................................................................................................................................................................................................................................................................................................................................S.............................................................S....
     Running test_cpp_utils.R:: .S............
     Testing ddhazard w/ generic things and w/ the the EKF : .....................S................
     Testing design_mat_and_risk_obj: ............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
     Testing fixed_effects_in_E_step: .........
     Testing test_fixed_effects_in_M_step: ..........S..
     Testing 'get_start_values': ....................
     Running tests for hatvalues: ....
     Testing examples in man files: .......S.S....SSSS........S
     Testing loglike: ........................
     Testing options: .
     Testing parallelglm vs. glm: ................................................S
     Testing plot functions: ......................................
     Testing predict: ...............................................................................SS
     Testing print function: ...SS.....
     Testing residuals functions: ..................................................................................................................................................................................................SS
     Testing shiny app: ..
     Testing static_glm: .............................
     Testing summary function: .................
     Testing test_utils: ............S......................................
     Testing weights in fit: ................
    
     ══ Skipped ═════════════════════════════════════════════════════════════════════
     1. PF_smooth gives same results (@test_PF.R#71) - On CRAN
    
     2. Import and export PF cloud from Rcpp gives the same (@test_PF.R#249) - On CRAN
    
     3. PF_EM gives previous results on head neck data set (@test_PF.R#342) - On CRAN
    
     4. PF_EM gives previous results on head neck data set with fixed effects and the logit model (@test_PF.R#409) - On CRAN
    
     5. compute_PF_summary_stats gives previous results (@test_PF.R#434) - On CRAN
    
     6. 'get_cloud_means' and 'get_cloud_quantiles' gives previous results (@test_PF.R#508) - On CRAN
    
     7. 'get_ancestors' yields the correct result (@test_PF.R#558) - On CRAN
    
     8. ´est_params_dens´ gives the same as a R version (@test_PF.R#580) - On CRAN
    
     9. fixed effect estimation gives the same as an R implementation (@test_PF.R#628) - On CRAN
    
     10. A few iterations with `type = "VAR"' yields the same as before (@test_PF.R#709) - On CRAN
    
     11. PF_EM gives the same with restricted and unrestricted model when we estimate all the parameters (@test_PF.R#778) - On CRAN
    
     12. Using `n_smooth_final` works as expected and yields previous results (@test_PF.R#883) - On CRAN
    
     13. sampling with a t-distribution gives previous results (@test_PF.R#949) - On CRAN
    
     14. 'PF_forward_filter' gives the same as 'PF_EM' when it should (@test_PF.R#987) - On CRAN
    
     15. 'state_fw' gives correct results (@test_PF.R#1116) - !dir.exists("pf-internals")
    
     16. 'state_bw' gives correct results (@test_PF.R#1152) - !dir.exists("pf-internals")
    
     17. 'artificial_prior' gives correct results (@test_PF.R#1187) - !dir.exists("pf-internals")
    
     18. 'observational_cdist' gives correct results (@test_PF.R#1221) - !dir.exists("pf-internals")
    
     19. combining forward and backwards works (@test_PF.R#1266) - !dir.exists("pf-internals")
    
     20. combining prior and backwards works (@test_PF.R#1313) - !dir.exists("pf-internals")
    
     21. mode approximations give expected result (@test_PF.R#1351) - !dir.exists("pf-internals")
    
     22. 'PF_get_score_n_hess' gives the same as an R implementation (@test_PF.R#1493) - On CRAN
    
     23. boot yields previously computed values with pbc (@test_boot_est.R#19) - On CRAN
    
     24. cloglog function gives previous result with simulated data using PF_EM and PF_forward_filter (@test_cloglog.R#56) - On CRAN
    
     25. mvrnorm gives expected sample mean and variance (@test_cpp_sample_funcs.R#50) - On CRAN
    
     26. 'mvtrnorm' yields close to uniform sample (@test_cpp_sample_funcs.R#111) - On CRAN
    
     27. trunc_lp_in_exponential_dist does not truncate when not needed (@test_cpp_utils.R#12) - On CRAN
    
     28. Different non-integer time_scales gives the same result with ddhazard (@test_ddhazard_n_EKF.R#165) - On CRAN
    
     29. posterior_approx gives previous found values with fixed effects in M-step (@test_fixed_effects_in_M_step.R#187) - On CRAN
    
     30. residuals.ddhazard help page examples gives the same results (@test_help_page_examples.R#43) - On CRAN
    
     31. ddhazard_boot help page examples gives the same results (@test_help_page_examples.R#67) - On CRAN
    
     32. PF_EM help page example runs and gives previous computed results (@test_help_page_examples.R#129) - On CRAN
    
     33. Second example on PF help page gives the same result (@test_help_page_examples.R#170) - On CRAN
    
     34. example in 'PF_EM' with gives previous results w/ a few iterations (@test_help_page_examples.R#226) - On CRAN
    
     35. `PF_forward_filter` the results stated in the comments and does not alter the .Random.seed as stated on the help page (@test_help_page_examples.R#357) - On CRAN
    
     36. 'PF_get_score_n_hess' gives previous results (@test_help_page_examples.R#515) - On CRAN
    
     37. glm and parallelglm gives the same (@test_parallelglm.R#80) - On CRAN
    
     38. Terms from predict with exponential outcome are correct (@test_predict.R#413) - On CRAN
    
     39. Different non-integer time_scales gives the same result with predict results (@test_predict.R#474) - On CRAN
    
     40. print.ddhazard_boot gives the expected output (@test_print.R#39) - On CRAN
    
     41. Print function for PF objects gives previous results (@test_print.R#89) - On CRAN
    
     42. Gets previous results with Rossi (@test_residuals.R#209) - On CRAN
    
     43. Get prevoius residuals with whas500 (@test_residuals.R#236) - On CRAN
    
     44. Testing util functions to sim series for tests (@test_test_utils.R#28) - On CRAN
    
     ══ Failed ══════════════════════════════════════════════════════════════════════
     ── 1. Failure: type = 'VAR' works with non-zero mean with a single term and give
     pf_Fear[!names(pf_Fear) %in% "clouds"] has changed from known value recorded in './previous_results/PF_VARS_non_zero_mean_inter.RDS'.
     Component "fixed_effects": Mean relative difference: 0.001930001
     Component "Q": Mean relative difference: 0.01270906
     Component "F": Mean relative difference: 0.05605184
     Component "EM_ests": Component "fixed_effects": Mean relative difference: 0.0009749454
     Component "EM_ests": Component "F": Mean relative difference: 0.03745616
     Component "EM_ests": Component "Q": Mean relative difference: 0.006622783
     Component "log_likes": Mean relative difference: 4.139832e-06
     Component "effective_sample_size": Component "forward_clouds": Mean relative difference: 4.012493e-05
     Component "effective_sample_size": Component "backward_clouds": Mean relative difference: 0.04364401
     ...
    
     ── 2. Failure: type = 'VAR' works with non-zero mean with a single term and give
     pf_Fear[!names(pf_Fear) %in% "clouds"] has changed from known value recorded in './previous_results/PF_VARS_non_zero_mean_slope.RDS'.
     Component "fixed_effects": Mean relative difference: 0.00139435
     Component "Q": Mean relative difference: 0.0165244
     Component "F": Mean relative difference: 0.7438022
     Component "EM_ests": Component "fixed_effects": Mean relative difference: 0.0007555823
     Component "EM_ests": Component "F": Mean relative difference: 0.6410284
     Component "EM_ests": Component "Q": Mean relative difference: 0.01026895
     Component "log_likes": Mean relative difference: 3.621962e-05
     Component "effective_sample_size": Component "forward_clouds": Mean relative difference: 0.002552145
     Component "effective_sample_size": Component "backward_clouds": Mean relative difference: 0.1172655
     ...
    
     ══ DONE ════════════════════════════════════════════════════════════════════════
     Error: Test failures
     Execution halted
Flavor: r-patched-solaris-x86

Version: 0.6.4
Check: whether package can be installed
Result: ERROR
    Installation failed.
Flavor: r-oldrel-osx-x86_64