Changes from Version 0.40-13 to 0.50-1 [13-Mar-2013]

* The functions npudist() and npudistbw() are now uncoupled from npudens
  and npudensbw (previously they relied on unconditional PDF bandwidths
  due to the lack of a multivariate mixed-data method for selecting bandwidths
  for CDFs - now with Li & Racine (2013) we have a robust method hence the
  split)

* The use of cdf=TRUE is deprecated for npudens and
  npudensbw objects due to the uncoupling described above

* Fixed glitch in gradient standard errors in npindex where identical
  standard errors were output in model$gerr

* Fixed glitch in covariance matrix in npindex (ichimura) where covariance
  matrix was not symmetric

* Fixed glitch in npksum() where use of bwtype="adaptive_nn" and
  operator="integral" produced the survivor function rather than
  the cumulative distribution function

* Cleaned up internals for npcmstest()

* Using .onUnload rather than .Last.lib in zzz.R

* Fixed glitch in npreg() summary where `Residual standard error' was
  reporting residual variance

* npksum() functionality extended

- npksum() can now return the matrix of kernel weights (which can be
  useful for constrained estimation, by way of illustration, or
  constructing novel kernel-based procedures without the need to write
  extensive code)

- npksum() can now accept different operators on a product kernel, for
  example,

  npksum(txdat=data.frame(x1,x2),operator=c("derivative","normal"),bws=c(1,1))

  will use the derivative kernel for x1 (i.e. the derivative of the
  gaussian kernel) and the default kernel for x2 (i.e. a standard
  kernel such as the gaussian) thereby allowing the user to program a
  number of estimators such as conditional CDFs etc. that were
  previously not available via npksum()

* Fixed glitch with variable scope where certain objects could not be
  found in the environment

* Added function `npcopula()' for d-dimensional copula estimation via
  inversion

* Modified stopping rules in npregiv and npregivderiv

* Added reference to R2 measure (Doksum and Samarov (1995))

* Startup message points to the faq, faq is now a vignette

Changes from Version 0.40-12 to 0.40-13 [05-Mar-2012]

* Added new function npregivderiv() that implements the IV derivative
  method of Florens and Racine (2012)

* Added more passable parameters to npregiv() (multistarting,
  parameters passed to optim() for cross-validation)

* Changes to code to improve compliance with R `Writing portable
  packages' guidelines and correct partial argument matches

Changes from Version 0.40-11 to 0.40-12 [24-Nov-2011]

* Added option (user request) to hold the bandwidth fixed but optimize
  the parameters in the single index model

Changes from Version 0.40-10 to 0.40-11 [24-Oct-2011]

* Corrected regression in single index errors

Changes from Version 0.40-9 to 0.40-10 [24-Oct-2011]

* Modified Silverman's adaptive measure of spread to reflect changes
  in sd() (sd on matrix deprecated)

Changes from Version 0.40-8 to 0.40-9 [30-July-2011]

* Renamed COPYING file to COPYRIGHTS

Changes from Version 0.40-7 to 0.40-8 [29-July-2011]

* Fixed issue where calling npplot resets system seed

* Updated examples in docs so that plot is recommended throughout (and
  not npplot that is invoked by plot)

* Fixed regression in npindex when gradients=TRUE and errors=TRUE

* Function npindex/npindexbw now accepts additional arguments and
  implements this properly (i.e. proper implementation by Tristen of
  Version 0.30-8/0.30-9 change for npindex)

* Function npplreg now supports factors in the parametric part just
  like lm() does

* Fixed glitch in jksum.c where the use of weights and adaptive bws
  could segfault.

Changes from Version 0.40-6 to 0.40-7 [8-Jun-2011]

* Function npregiv now supports exogenous X and multivariate Z and W.

* demo(npregiv) provides a useful illustration.

Changes from Version 0.40-5 to 0.40-6 [1-Jun-2011]

* Added a new function npregiv that conducts nonparametric
  instrumental regression a la Darolles, Fan, Florens and Renault
  (2011, forthcoming, Econometrica) and Horowitz (2011,
  Econometrica). Note that this function currently returns the fitted
  phi(z) (i.e. lacks much functionality relative to other np
  functions) and is in `beta status' until further notice.

* Added a new dataset `Engel95' that allows one to estimate Engel
  curves using the new nonparametric instrumental regression function
  npregiv.

Changes from Version 0.40-4 to 0.40-5 [26-Apr-2011]

* Fixed issue with npindexbw where, for certain problems, starting
  values needed refinement otherwise convergence would fail (we now
  use an improved normalization for the starting values)

Changes from Version 0.40-3 to 0.40-4 [21-Jan-2011]

* Fixed issue with ckertype and ckerorder not being propagated in
  np.singleindex.bw.R

* Fixed issue with negative penalties being returned by cv.aic in
  npregbw (ought to have been +infinity)

Changes from Version 0.40-1 to 0.40-3 [23-Jul-2010]

* Added random seed (defaults to 42) to npscoefbw to ensure consistent
  values for optimization for successive invocations on the same data

* Fixed glitch in multistarting in npscoefbw whereby multistarting was
  not working (always returned last computed function value and not
  the minimum)

* Fixed issue for npRmpi where the C code underlying regression
  cross-validation (code in jksum.c) differs between np and npRmpi
  (both were correct with the latter being a tad slower, now both use
  unified code base)

* Fixed a scope issue whereby a user would write a function that calls
  an np/npRmpi command, however, objects passed to the user's function
  and called by the np/npRmpi command (i.e. such as newdata) cannot be
  found in the environment yet they exist outside of the function

* Fixed issue with bwscaling=TRUE and bwmethod="cv.aic" in npreg

Changes from Version 0.40-0 to 0.40-1 [4-Jun-2010]

* Added asymptotic standard errors to npindex for the Klein and Spady
  and Ichimura parameter estimates which, when gradients=TRUE, can be
  extracted via vcov(foo) where foo is a npsingleindex object (the
  Z-scores can be obtained via Z<-coef(foo)[-1]/sqrt(diag(vcov(foo)))[-1])

Changes from Version 0.30-9 to 0.40-0 [25-May-2010]

* Modified codebase to enable dynamic spawning for interactive
  sessions in npRmpi

* Interactive examples supported in npRmpi

Changes from Version 0.30-8 to 0.30-9 [17-May-2010]

* Fixed issue where ukertype and okertype were being ignored by npindex

* Fixed regression (dating to version 0.30-4) where random.seed=42 was
  not initialized in functions npcmstest, npdeneqtest, npindexbw,
  npsdeptest, npqcmstest, npsigtest, npsymtest, npunitest, and npplot

* Fixed issue with saving and restoring random seed in npdeptest

* Changes to codebase to modify method used to prevent division by
  zero

* New vignette for the npRmpi package (vignette("npRmpi",package="npRmpi"))

Changes from Version 0.30-7 to 0.30-8 [20-Apr-2010]

* Implemented moment version of metric entropy in npsymtest and
  npunitest with warnings about their use documented carefully and
  exceptions trapped and warnings issuing when detected
 
* Cleaned up print/summary output formatting of some functions

Changes from Version 0.30-6 to 0.30-7 [15-Feb-2010]

* Added function npunitest for entropy-based testing of equality of
  univariate densities as described in Maasoumi and Racine (2002,
  2009)

* Updated vignette to reflect new functions (Table 1: np functions)

Changes from Version 0.30-5 to 0.30-6 [3-Feb-2010]

* Added function npsdeptest for entropy-based testing of nonlinear
  serial dependence described in Granger, Maasoumi and Racine (2004)

* Added function npdeptest for entropy-based testing of nonlinear
  pairwise dependence described in Maasoumi and Racine (2002)

* Added more bootstrap options to npsymtest (now both iid and
  time-series bootstrapping are supported)

* Cleaned up summary formatting in the vignette by adding
  \usepackage[utf8x]{inputenc} to the Sweave file np.Rnw

* Fixed issue with saving and restoring random seed when there was
  none in the environment

Changes from Version 0.30-4 to 0.30-5 [29-Jan-2010]

* Added function npdeneqtest for integrated squared difference testing
  of equality of densities as described in Maasoumi, Li, and Racine
  (2009), Journal of Econometrics

* Save random seed prior to setting seed in certain functions, then
  restore seed after function completes

Changes from Version 0.30-3 to 0.30-4 [27-Jan-2010]

* Added function npsymtest for entropy-based testing of symmetry
  described in Maasoumi and Racine (2009), Econometric Reviews

* Added function b.star that automates block length selection for
  the stationary and circular bootstrap

* Cleaned up docs

Changes from Version 0.30-2 to 0.30-3 [29-May-2009]

* Corrected error in Epanechnikov convolution kernels for fixed and
  generalized bandwidth objects

* Changed default example in npscoef

Changes from Version 0.30-1 to 0.30-2 [19-Apr-2009]

* min(std,IQR/1.348) is the adaptive measure of spread. We now test
  for the pathological case where IQR is zero but std > 0 and return
  std in this instance

Changes from Version 0.30-0 to 0.30-1 [29-Jan-2009]

* predict now supports bandwidth, density, distribution, conbandwidth,
  condensity, and condistribution objects

* Consistently allow predictions for categorical values outside of
  support of training data

  Note that predictions based upon unconditional density objects
  defined over categorical variables that lie outside the support of
  the training data may no longer be true probabilities (i.e., as
  defined over the training data and the extended/augmented support --
  their sum may exceed one) and may therefore require renormalization
  by the user 

* Fixed a numerical issue which could hinder npregbw()'s cross
  validation with higher-order kernels

* Default nmulti in npplregbw() is now set correctly

* Fixed a bug with the ridging routine in npscoefbw(), added ridging to
  npscoef

* Fixed trivial i/o issue with "Multistart 1 of" using npscoefbw()

Changes from Version 0.20-4 to 0.30-0 [15-Jan-2009]

* Added basic user-interrupt checking for all underlying C code so
  that either <Ctrl-C> (Rterm) or the `STOP' icon (Rgui) will
  interrupt all running processes. This has a number of desirable side
  effects in addition to being able to interrupt C-based processes
  including i) R no longer showing up as `not responding' under the
  task manager (Windows) or the activity monitor (Mac OS X) and ii)
  buffered output now being correctly displayed when using Rgui under
  Windows and Mac OS X

  Note that repeated interruption of large jobs can reduce available
  memory under R - if this becomes an issue (i.e., you get a `cannot
  allocate...' error under R) simply restart R (i.e., exit then run a
  fresh R session)

* Added a function npseed() that allows the user to set/reset the
  random seed for all underlying C routines

* Fixed a bug that caused npplregbw() to ignore any kernel options
  for the regression of y on z

* Refined certain constants used in the normal-reference density
  bandwidth rule for increased accuracy

* Moved from using the maximum likelihood estimate of variance
  throughout to the degrees of freedom corrected estimate (all
  variance estimates now change by the factor (n-1)/n)

Changes from Version 0.20-3 to 0.20-4 [19-Nov-2008]

* Using an adaptive measure of spread throughout.  The scale factor
  reported for a bandwidth can appear to be small when the standard
  deviation is inflated due to the presence of outliers.  Furthermore,
  supplying a scale factor of, say, 1.06 for density estimation when
  there are outliers that inflate the standard deviation may
  oversmooth rather dramatically in the presence of outliers.  We now
  use the measure found in Silverman (1986, equation (3.30)) which is
  min(standard deviation, interquartile range/1.349). This robust
  choice produces expected results for scale factors in the presence
  of outliers

Changes from Version 0.20-2 to 0.20-3 [14-Nov-2008]

* Fixed a typo which caused predict() and plot() to abort when called
  on plregression objects, and which also prevented print() and
  summary() from printing information about the kernels used when
  called on plregression objects

* Fixed a typo which caused partially linear regressions to crash when
  out-of-sample responses were provided with evaluation data

Changes from Version 0.20-1 to 0.20-2 [02-Nov-2008]

* Allow for evaluation outside of discrete support of factors in
  npksum() and fixed a warning in jksum

* Fixed a bug which lead to unpredictable behavior when there were
  more categorical values for the training data than realisations

Changes from Version 0.20-0 to 0.20-1 [13-Aug-2008]

* Work-around for scale-factor issues during npregbw() cv when
  changing the training data

Changes from Version 0.14-3 to 0.20-0 [28-Jul-2008]

* npksum() now supports an expanded set of kernels (including
  convolution, derivative and integral), which can be selected via the
  'operator' argument

* Automatic bandwidth searches are now performed when attempting to
  evaluate on data without bandwidths. This allows users to combine
  bandwidth selection and estimation in one step

* The npsigtest() interface is brought in line with other functions
  (S3)

* Significance tests can now be performed on npreg() outputs, so
  npsigtest(modelname) is now supported

* Added a vignette and faq. To see the vignette try
    vignette("np",package="np")

* summary() on npconmode() now properly retrieves names from bandwidth
  objects

* Fixed the 6th and 8th order epanechnikov kernels

* Fixed some quietness issues

* npplot() now returns data upon request for conditional densities

* npreg() and npcdens() now take the appropriate limits in some
  pathological cases

* User supplied bandwidths now operate seamlessly with the formula
  interface

Changes from Version 0.14-2 to 0.14-3 [02-May-2008]

* Fixed a glitch that only arose when using the `liracine' unordered
  kernel in the presence of irrelevant variables. The upper bound for
  numerical search was constrained to be (c-1)/c [that for the
  aitchisonaitken unordered kernel] but ought to have been 1. The
  summary output would therefore show a value of lambda hitting the
  (smaller) upper bound (c-1)/1 when it may have hit the (larger)
  upper bound 1

Changes from Version 0.14-1 to 0.14-2 [11-Jan-2008]

* Relaxed checking tolerances slightly to prevent spurious 'invalid
  bandwidth' errors

* Empty sections were removed from help files

* example(foobar) now works again. This was disabled in 0.14-1 at the
  request of the R maintainers in order to shorten the duration of R
  CMD check. All examples remained in the help files but due to the
  presence of `dontrun' they were not run when examples(foobar) is
  requested. Now a limited subset are run while the full set of
  examples remain in the documents

Changes from Version 0.13-1 to 0.14-1 [18-Dec-2007]

* Now use optim for minimisation in single index and smooth
  coefficient models

* Fixed bug in klein-spady objective function

* Standard errors are now available in the case of no continuous
  variables

* Summary should look prettier, print additional information

* Tidied up lingering issues with out-of-sample data and conditional
  modes

* Fixed error when plotting asymptotic errors with conditional
  densities

* Fixed a bug in npplot() with partially linear regressions and
  plot.behavior='data' or 'plot-data'

* Maximum default number of multistarts is 5

* Least-squares cross-validation of conditional densities uses a new,
  much faster algorithm

* New, faster algorithm for least-squares cross-validation for both
  local-constant and local linear regressions

  Note that the estimator has changed somewhat: both cross-validation
  and the estimator itself use a method of shrinking towards the local
  constant estimator when singularity would otherwise lead to the
  breakdown of the estimator. This arises in sparse data settings in
  conjunction with small bandwidths for one or more regressor

* Optimised smooth coefficient code, added ridging

* Fixed bug in uniform CDF kernel

* Fixed bug where npindexbw() would ignore bandwidth.compute = FALSE
  and compute bandwidths when supplied with a preexisting bw object

* Now can handle estimation out of discrete support

* Summary would misreport the values of discrete scale factors which
  were computed with bwscaling = TRUE

Changes from Version 0.12-1 to 0.13-1 [03-May-2007]

* Bandwidths are now checked for validity based on their variable and
  kernel types

* np now does a better job of preserving names of some 'y' data

* Names of coefficients returned from coef() now match variable names

* Fixed some corner cases in npksum() involving the dimensionality of
  outputs

* Fixed deprecation warnings in R 2.5.0 caused by use of $ on atomic
  objects

* Various and sundry bug fixes in npscoef()

* npscoef() now handles discrete 'z' data

* Predict now accepts the argument 'se.fit', like predict.lm

* Fixed bug where incorrect asymptotic standard errors of gradients
  for regression objects were being displayed in npplot()

* Fixed bug where errors of gradients of regression objects were not
  being returned in matrix form

* vcov() now works with partially linear regression objects

* Fixed detection of evaluation responses when using the formula
  interface

* Pre-computed bandwidth objects are now provided for some of the more
  computationally burdensome examples

* Added Jeffrey Wooldridge's WAGE1 dataset with qualitative variables
  (married, female, nonwhite)

* Predictions outside of discrete support for regressions and
  conditional densities are now allowed

* Fixed sign issue with scaling of standard errors in the single index
  model

* Fixed error when calculating some bandwidths/scale factors for
  display purposes

* Bug in passing certain arguments to npcdensbw() fixed

* Added predict method for qregression objects

* Proper normalisation for liracine kernel shown in summary

* Fixed output bug ($\hat ~$H) in summary method for sigtest objects

* Fixed regression with plotting of bootstrapped errors in perspective
  plots

* npcdist() no longer incorrectly calls npcdens()

* Fixed spacing between var name and p-value in significance test
  summaries

Version 0.12-1 [19-Nov-2006]

* Initial release of the np package on CRAN