Saves information from a zero-inflated regression model for count data with excess zeros fitted by R0INFLATED (D.A. Murray).
Options
RESIDUALS = variate |
Saves the simple residuals |
|---|---|
FITTEDVALUES = variate |
Saves the fitted values |
ESTIMATE = variate |
Saves the parameter estimates |
SE = variate |
Saves the standard errors of the parameter estimates |
VCOVARIANCE = symmetric matrix |
Saves the variance-covariance matrix of estimates for the ZIP, ZIB and ZINB models |
XFITTEDVALUES = variate |
Saves the fitted values for the count model |
XSEFITTEDVALUES = variate |
Saves the standard errors of the fitted values for the fitted values of the count model |
ZFITTEDVALUES = variate |
Saves the fitted values for the zero model |
ZSEFITTEDVALUES = variate |
Saves the standard errors of the fitted values for the fitted values of the zero model |
_2LOGLIKELIHOOD = scalar |
Saves -2 times the log-likelihood |
AIC = scalar |
Saves the Akaike information coefficient |
SIC = scalar |
Saves the Schwarz (Bayesian) information coefficient |
No parameters
Description
This procedure allows you to copy information into Genstat data structures from a model that has been fitted to count data with excess zeros by procedure R0INFLATED. You do not need to declare the structures in advance; Genstat will declare them automatically to be of the correct type and length.
The RESIDUALS and FITTEDVALUES options save the simple residuals and the fitted values. The ESTIMATES and SE options save the parameter estimates and their standard errors. The VCOVARIANCE option saves the variance-covariance matrix of estimates from either a ZIP or ZINB model. The ZFITTEDVALUES and ZSEFITTEDVALUES options save the fitted values and standard errors of fitted values for the zero state. Similarly, the XFITTEDVALUES and XSEFITTEDVALUES options save the fitted values and standard errors of fitted values for the count state. The _2LOGLIKELIHOOD option saves -2 times the log-likelihood, and the AIC and SIC options save the Akaike and Schwarz (Bayesian) information coefficients respectively.
Options: RESIDUALS, FITTEDVALUES, ESTIMATES, SE, VCOVARIANCE, XFITTEDVALUES, XSEFITTEDVALUES, ZFITTEDVALUES, ZSEFITTEDVALUES, _2LOGLIKELIHOOD, AIC, SIC.
Parameters: none.
See also
Procedure: R0INFLATED.
Commands for: Regression analysis.
Example
CAPTION 'R0KEEP example - EM algorithm',\
!t('Apple shoot data: Ridout et al.',\
'Models for count data with many zeros, IBC Cape Town 1998');\
STYLE=meta,plain
FACTOR [LABELS=!T('0.5','1','2','4'); VALUES=30(1,2),\
40(3,4),30(1,2,3),40(4)] Hormone
FACTOR [LABELS=!T('8','16'); VALUES=140(1),130(2)] Period
READ NShoots
1 1 1 2 2 3 3 3 4 4 4 4 4 4 5 5 5 6 6 7 7 8 8 8 9 10 10 11 13 17
2 2 2 4 6 6 6 7 7 7 7 7 7 7 8 8 8 9 9 9 9 9 10 10 10 11 11 11 11 13
2 3 3 4 4 4 4 5 5 5 5 6 6 6 6 7 7 7 7 8
8 8 8 8 8 8 9 9 9 9 9 10 10 10 10 11 12 12 14 14
0 0 3 3 4 4 5 5 5 5 5 6 6 6 6 6 7 7 7 7
8 8 8 8 8 8 8 8 9 9 9 10 10 10 10 11 11 11 11 14
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 3 3 4 5 5 6 8 9 9 9 10 11 12
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 3 4 4 5 6 6 8 10 10 10 12
0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 2 2 3 4 4 5 5 6 6 6 7 9 9 11 12
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 2 2 3 3 3 3 4 4 4 5 6 6 6 6 7 7 7 9 9 :
R0INFLATED [PRINT=mod,est,sum; CONSTANT=estimate; XTERMS=Hormone*Period; \
ZCONSTANT=estimate; ZTERMS=Period] NShoots
R0KEEP [ESTIMATES=est; SE=se; VCOVARIANCE=vcov]
PRINT est,se
PRINT vcov
CAPTION 'R0KEEP example - Conditional Model',\
!t('Leadbeater''s Possum data: Welsh et al.',\
'Modelling the abundance of rare species: statistical models ',\
'for counts with extra zeros. Ecological Modelling');\
STYLE=meta,plain
DELETE [REDEFINE=yes] no_lb,stags,lstags
VARIATE [NVALUES=151] no_lb,stags
READ no_lb
7 0 0 3 2 10 7 3 0 0 0 0 0 2 0 1 0 4 3 2 10 7 0 3 7 0
0 0 0 0 5 9 0 0 0 0 1 0 5 4 0 0 4 0 4 0 2 0 0 1 1 0
3 0 0 0 0 0 2 0 0 1 0 2 5 3 0 0 0 0 0 0 0 0 5 0 0 0
0 0 0 1 5 4 0 0 0 0 3 0 3 3 1 0 0 0 0 0 2 0 0 1 0 3
0 0 4 0 0 3 4 0 8 5 3 0 0 0 5 5 0 2 0 0 0 0 0 2 0 2
0 0 0 0 0 4 0 0 0 0 5 0 0 0 0 0 1 0 0 0 0 :
READ stags
12 15 6 14 16 16 9 20 7 4 6 5 4 6 4 10 6 11 11 4 16 8 10 9 7 10
15 5 7 10 11 8 8 3 14 5 8 14 11 2 1 1 7 2 7 7 1 6 8 6 6 5
6 0 0 2 0 1 3 2 2 6 3 4 3 4 5 2 3 4 4 2 2 10 16 10 4 3
2 2 2 2 3 1 6 8 2 4 12 13 3 14 2 4 0 2 3 14 29 2 4 6 3 8
4 7 20 4 11 5 1 2 27 24 9 18 3 20 25 4 4 30 24 8 4 6 5 3 5 2
3 5 7 4 5 4 4 1 4 23 25 31 0 8 4 4 1 3 1 1 4 :
CALCULATE lstags = log(stags+1)
R0INFLATED [PRINT=mod,sum,est; METHOD=conditional;\
ZTERMS=lstags; XTERMS=lstags] no_lb
R0KEEP [RESIDUALS=res; FITTEDVALUES=fitted; ESTIMATES=estc; SE=sec]
PRINT estc,sec
PRINT res,fitted