ml.nb1 is a maximum likelihood function for estimating linear negative binomial (NB1) data. Output consists of a table of parameter estimates, standard errors, z-value, and confidence intervals.
● Data Source:
CranContrib
● Keywords: models
● Alias: ml.nb1
●
0 images
|
mytable is used to produce a table of frequencies, proportion and cumulative proportions for a count variable
● Data Source:
CranContrib
● Keywords: table
● Alias: myTable
●
0 images
|
ml.nb2 is a maximum likelihood function for estimating linear negative binomial (NB2) data. Output consists of a table of parameter estimates, standard errors, z-value, and confidence intervals.
● Data Source:
CranContrib
● Keywords: models
● Alias: ml.nb2
●
0 images
|
nb1_syn is a generic function for developing synthetic NB1 data and a model given user defined specifications.
● Data Source:
CranContrib
● Keywords: models, negative binomial
● Alias: nb1_syn
●
0 images
|
modelfit is used following a glm() or glm.nb() model to produce a list of model fit statistics.
● Data Source:
CranContrib
● Keywords: models
● Alias: modelfit
●
0 images
|
nbc_syn is a generic function for developing synthetic NB-C data and a model given user defined specifications.
● Data Source:
CranContrib
● Keywords: models, negative binomial
● Alias: nbc_syn
●
0 images
|
nb2_syn is a generic function for developing synthetic NB2 data and a model given user defined specifications.
● Data Source:
CranContrib
● Keywords: models, negative binomial
● Alias: nb2_syn
●
0 images
|
ml.pois is a maximum likelihood function for estimating Poisson data. Output consists of a table of parameter estimates, standard errors, z-value, and confidence intervals. An offset may be declared as an option.
● Data Source:
CranContrib
● Keywords: models
● Alias: ml.pois
●
0 images
|
probit_syn is a generic function for developing synthetic probit regression data and a model given user defined specifications.
● Data Source:
CranContrib
● Keywords: binomial, models, probit
● Alias: probit_syn
●
0 images
|
poi.obs.pred is used to produce a table of a Poisson model count response with mean observed vs mean predicted proportions, and their difference.
● Data Source:
CranContrib
● Keywords: table
● Alias: poi.obs.pred
●
0 images
|