Packaged: 2019-02-01 16:05:58 UTC; Catherine

Packaged: 2019-04-07 09:26:49 UTC; Catherine

Description: To fit the kernel semi-parametric model and its extensions. It allows multiple kernels and unlimited interactions in the same model. Coefficients are estimated by maximizing a penalized log-likelihood; penalization terms and hyperparameters are estimated by minimizing leave-one-out error. It includes predictions with confidence/prediction intervals, statistical tests for the significance of each kernel, a procedure for variable selection and graphical tools for diagnostics and interpretation of covariate effects. Currently it is implemented for continuous dependent variables. The package is based on the paper of Liu et al. (2007), <doi:10.1111/j.1541-0420.2007.00799.x>.

Title: Lilliefors-Corrected Kolmogorov-Smirnoff Goodness-of-Fit Tests
Author: Phil Novack-Gottshall, Steve C. Wang
Description: Implements the Lilliefors-corrected Kolmogorov-Smirnoff test for use
in goodness-of-fit tests, suitable when population parameters are unknown and
must be estimated by sample statistics. P-values are estimated by simulation.
Can be used with a variety of continuous distributions, including normal,
lognormal, univariate mixtures of normals, uniform, loguniform, exponential,
gamma, and Weibull distributions. Functions to generate random numbers and
calculate density, distribution, and quantile functions are provided for use
with the log uniform and mixture distributions.
Packaged: 2016-03-18 17:15:41 UTC; pnovack-gottshall

Title: Lilliefors-Corrected Kolmogorov-Smirnov Goodness-of-Fit Tests
Description: Implements the Lilliefors-corrected Kolmogorov-Smirnov test for use
Packaged: 2018-03-04 17:14:35 UTC; pnovack-gottshall

Packaged: 2018-08-14 21:01:54 UTC; pnovack-gottshall

Packaged: 2019-07-03 19:01:26 UTC; pnovack-gottshall

Title: Computing P-Values of the K-S Test for (Dis)Continuous Null
Author: Dimitrina S. Dimitrova <D.Dimitrova@city.ac.uk>
Copyright: Copyright holders of FFTW3: Copyright (c) 2003, 2007-11
Matteo Frigo; Copyright (c) 2003, 2007-11 Massachusetts
Description: Computes a p-value of the one-sample two-sided (or one-sided, as a special case) Kolmogorov-Smirnov (KS) statistic, for any fixed critical level, and an arbitrary, possibly large sample size for a pre-specified purely discrete, mixed or continuous cumulative distribution function (cdf) under the null hypothesis. If a data sample is supplied, 'KSgeneral' computes the p-value corresponding to the value of the KS test statistic computed based on the user provided data sample. The package 'KSgeneral' implements a novel, accurate and efficient method named Exact-KS-FFT, expressing the p-value as a double-boundary non-crossing probability for a homogeneous Poisson process, which is then efficiently computed using Fast Fourier Transform (FFT). The package can also be used to compute and plot the complementary cdf of the KS statistic which is known to depend on the hypothesized distribution when the latter is discontinuous (i.e. purely discrete or mixed).