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KSPM (version 0.2.1)

Kernel Semi-Parametric Models

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), .

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Version

Install

install.packages('KSPM')

Monthly Downloads

156

Version

0.2.1

License

GPL-3

Maintainer

Catherine Schramm

Last Published

August 10th, 2020

Functions in KSPM (0.2.1)

derivatives

Computing kernel function derivatives
csm

Conventional and Social media features of 187 movies.
cooks.distance.kspm

Cook's distance for a Kernel Semi Parametric Model Fit
deviance.kspm

Model deviance
Kernel

Create a Kernel Object
case.names.kspm

Case names of fitted models
kernel.list

List of kernel parts included in the kernel semi parametric model
kernel.method

some internal methods in computation of kernel semi parametric model
extractAIC.kspm

Extract AIC from a Kernel Semi Parametric Model
energy

Energy consumption measuring hourly during 22 days
kspm

Fitting Kernel Semi Parametric model
kspmControl

Control various aspects of the optimisation problem
get.parameters

compute Kernel Semi Parametric model parameters
hypercoef

Extract Model Hyper-parameter
coef.kspm

Extract Model Coefficients
logLik.kspm

Log Likelihood of a kspm Object
kernel.function

Kernel Functions
info.kspm

Giving information about Kernel Semi parametric Model Fits
residuals.kspm

Extract residuals from a Kernel Semi Parametric Model
rstandard.kspm

Standardized residuals for Kernel Semi parametric Model Fits
confint.kspm

Confidence interavls for linear part of model parameters
test.function

Score Tests for kernel part in kernel semi parametric model
predict.kspm

Predicting Kernel Semi parametric Model Fits
fitted.kspm

Extract Model Fitted values
kernel.matrix

Kernel matrix
plot.derivatives

Plot derivatives of a kspm object
plot.kspm

Plot Diagnostics for a kspm Object
search.parameters

Optimisation to cumpute hyperparameter in Kernel Semi Parametric model
print.kspm

Print results from a Kernel Semi parametric Model Fit
sigma.kspm

Extract residuals standard deviation
lossFunction.looe

Computation of the leave one out error (LOOE) in kernel semi parametric model
nobs.kspm

Extract the number of observations from a Kernel Semi parametric Model Fit
flexible.summary

Summarizing Kernel Semi parametric Model Fits with flexible parameters for Davies' approximation method
summary.kspm

Summarizing Kernel Semi parametric Model Fits
stepKSPM

Choose a model by AIC or BIC in a Stepwise Algorithm
variable.names.kspm

Variable names of fitted models