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

* Corrected 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

* NB: 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
