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Last data update: 2014.03.03

R: Add All Possible Single Terms to a GWRM Model

add1.gw

R Documentation

Add All Possible Single Terms to a GWRM Model

Description

Compute all the single terms in the scope argument that can be added to the GWRM model, fit those models and compute a table of the changes in fit.

Usage

## S3 method for class 'gw'
add1(object, scope, test = c("none", "Chisq"), k = 2,
  trace = FALSE, ...)

Arguments

`object`	a fitted object of class inheriting from `"gw"`.
`scope`	a formula giving the terms to be considered for adding.
`test`	`"none"`, which considers the AIC criterion, or `Chisq`, which is the likelihood-ratio test.
`k`	the penalty constant in AIC / Cp.
`trace`	if `TRUE`, print out progress reports.
`...`	further arguments passed to or from other methods.

Value

An object of class "anova" summarizing the differences in fit between the models.

Examples

data(goals)
fit0 <- gw(goals ~ offset(log(played)), data = goals)
summary(fit0)

fit1 <- add1(fit0, ~ position)
summary(fit1)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(GWRM)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/GWRM/add1.gw.Rd_%03d_medium.png", width=480, height=480)
> ### Name: add1.gw
> ### Title: Add All Possible Single Terms to a GWRM Model
> ### Aliases: add1.gw
> 
> ### ** Examples
> 
> data(goals)
> fit0 <- gw(goals ~ offset(log(played)), data = goals)
> summary(fit0)

Call:  gw(formula = goals ~ offset(log(played)), data = goals)

Coefficients:
             Estimate   Std. Error  z value    Pr(>|z|) 
(Intercept)   -2.25269    0.04279   -52.63944    0.00000

Fit:
  log-likelihood  AIC    BIC    df   
  -2051            4108   4123   1221

betaII:
  par        Estimate   Std. Error
  k          12.951182  6.653273  
  ro          6.604384  2.131549  

Degrees of Freedom: Total (i.e. Null);  1221 Residual

Code of convergence: 0  

Method: L-BFGS-B 
> 
> fit1 <- add1(fit0, ~ position)
> summary(fit1)
       Df         AIC      
 Min.   :2   Min.   :3820  
 1st Qu.:2   1st Qu.:3892  
 Median :2   Median :3964  
 Mean   :2   Mean   :3964  
 3rd Qu.:2   3rd Qu.:4036  
 Max.   :2   Max.   :4108  
 NA's   :1                 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>