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hoa (version 2.1.2)

Higher Order Likelihood Inference

Description

Performs likelihood-based inference for a wide range of regression models. Provides higher-order approximations for inference based on extensions of saddlepoint type arguments as discussed in the book Applied Asymptotics: Case Studies in Small-Sample Statistics by Brazzale, Davison, and Reid (2007).

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Version

Install

install.packages('hoa')

Monthly Downloads

36

Version

2.1.2

License

GPL (>= 2) | file LICENCE

Homepage

http://www.r-project.org

Maintainer

Alex-Antoine Fortin

Last Published

July 14th, 2015

Functions in hoa (2.1.2)

Crying Babies Data

print.nlreg.contours

Use print() on a `nlreg.contours' object

plot.nlreg.profiles

Use plot() on a `profile.nlreg' and `all.profiles.nlreg' object

Support for `nlreg' package of `hoa' bundle

Diagnostics for Regression-Scale Models

Fit a Regression-Scale Model Without Computing the Model Matrix

print.family.rsm

Use print() on a ``family.rsm'' object

Nonlinear Heteroscedastic Model Object

nlreg.contours.object

Contour Object for Nonlinear Heteroscedastic Models

Use print() on a ``cond'' object

Use print() on a `mpl' object

Radioimmunoassay Data

Differentiate the Mean Function of a Nonlinear Model

family.rsm.object

Family Object for Regression-Scale Models

Compute the Log Likelihood for Nonlinear Heteroscedastic Models

Nonlinear Heteroscedastic Model Diagnostics

print.summary.mpl

Use print() on a `summary.mpl' object

residuals.nlreg

Use residuals() on a `nlreg' object

ANOVA Table for a RSM Object

`Daphnia Magna' Data

family.summary.cond

Use family() on a ``summary.cond'' object

Approximate Conditional Inference in Regression-Scale Models

Approximate Conditional Inference Object

Fraudulent Automobile Insurance Claims Data

Support for Functions rsm.fit and rsm.surv

rsm.distributions

RSM Family Support Object

Returns the Expected Information Matrix --- Generic Function

Likelihood-Based Confidence Intervals Based on fr Object

Regression-Scale Model Object

Summary Method for Objects of Class ``cond''

Approximate Conditional Inference - Generic Function

Expected Information Matrix for `nlreg' Objects

print.nlreg.profiles

Use print() on a `nlreg.profile' and `all.nlreg.profiles' object

Fit an Empty Regression-Scale Model

var2cor.nlregmpl

Use var2cor() on a `nlreg' and `mpl' object

summary.nlreg.profile

Summary Method for Objects of Class `nlreg.profile'

Fit a Regression-Scale Model Without Computing the Model Matrix

Six Herbicide Data Sets

Fungal Infections Treatment Data

Compute the Log Likelihood for Regression-Scale Models

Nuclear Power Station Data

plot.nlreg.contours

Use plot() on a `nlreg.contours' object

Returns the Observed Information Matrix --- Generic Function

print.summary.marg

Use print() on a ``summary.marg'' object

print.summary.nlreg

Use print() on a `summary.nlreg' object

Use print() on a `nlreg' object

Calculate Variance-Covariance Matrix for a Fitted RSM Model

Huber's Least Favourable Distribution

Differentiate the Variance Function of a Nonlinear Model

Use coef() on a `nlreg' object

House Price Data

Approximate Conditional Inference for Logistic and Loglinear Models

Maximum Adjusted Profile Likelihood Estimates for a `nlreg' Object

Fit a Nonlinear Heteroscedastic Model via Maximum Likelihood

Generate Plots for an Approximate Conditional Inference Object

plot.nlreg.diag

Diagnostic Plots for Nonlinear Heteroscedastic Models

Generate Plots for an Approximate Marginal Inference Object

Extract All Parameters from a Model --- Generic Function

Metsulfuron Methyl Data

Profile Method for `nlreg' Objects

Helicopter Data

Use param() on a `nlreg' object

Generate a RSM Family Object

print.summary.rsm

Use print() on a ``summary.rsm'' object

Use print() on a ``marg'' object

Fit a Regression-Scale Model

print.summary.nlreg.profiles

Use print() on a `summary.nlreg.profile' and `summary.all.nlreg.profiles' object

Summary Method for Regression-Scale Models

Update and Re-fit a RSM Model Call

Summary Method for Nonlinear Heteroscedastic Models

Use print() on a ``rsm'' object

summary.all.nlreg.profiles

Summary Method for Objects of Class `all.nlreg.profiles'

Convert Covariance Matrix to Correlation Matrix --- Generic Function

Use anova() on a ``rsmlist'' object

all.profiles.nlreg

Support for function `profile.nlreg'

Use fitted() on a `nlreg' object

contour.all.nlreg.profiles

Contour Method for `nlreg' Objects

nlreg.profile.objects

Profile Objects for Nonlinear Heteroscedastic Models

Use family() on a ``cond'' object

Use family() on a ``rsm'' object

Maximum Adjusted Profile Likelihood Estimation --- Generic Function

make.family.rsm

Support for RSM Family Functions

Plot a fr Object

Darwin's Data on Growth Rates of Plants

Compute Residuals for Regression-Scale Models

Diagnostic Plots for Regression-Scale Models

Summary Method for Objects of Class ``marg''

Summary Method for `mpl' Objects

Tangent exponential model: Higher Order Likelihood Approximation

Maximum Adjusted Profile Likelihood Object

Chlorsulfuron Data

AIDS Symptoms and AZT Use Data

Higher Order Likelihood Inference

Approximate Marginal Inference Object

Observed Information Matrix for `nlreg' Objects

print.summary.cond

Use print() on a ``summary.cond'' object