Last data update: 2014.03.03

R: Drop All Possible Single Terms to a GWRM Model
drop1.gwR Documentation

Drop All Possible Single Terms to a GWRM Model

Description

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

Usage

## S3 method for class 'gw'
drop1(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 dropping.

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 <- step(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.
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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/drop1.gw.Rd_%03d_medium.png", width=480, height=480)
> ### Name: drop1.gw
> ### Title: Drop All Possible Single Terms to a GWRM Model
> ### Aliases: drop1.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 <- step(fit0, ~ position)
Start:  AIC=4107.71
goals ~ offset(log(played))

trying +position
           Df    AIC
+ position  2 3820.0
<none>        4107.7

Step:  AIC=3819.98
goals ~ position + offset(log(played))

trying -position
           Df    AIC
<none>        3820.0
- position  2 4107.7
> summary(fit1)

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

Coefficients:
                    Estimate    Std. Error  z value     Pr(>|z|)  
(Intercept)         -3.092e+00   7.876e-02  -3.926e+01   0.000e+00
positionForward      1.568e+00   8.996e-02   1.743e+01   5.236e-68
positionMidfielder   6.835e-01   8.798e-02   7.768e+00   7.967e-15

Fit:
  log-likelihood  AIC    BIC    df   
  -1905            3820   3846   1219

betaII:
  par       Estimate  Std. Error
  k         13.79084  7.597486  
  ro        12.89112  4.229415  

Degrees of Freedom: Total (i.e. Null);  1219 Residual

Code of convergence: 0  

Method: L-BFGS-B 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>