cgetC

quadratic parameter (&gt;0 and less than 1)

items are on a scale from 1, &#8230;, k

<code>cgetC</code> obtains a list of censoring points, or cut-offs, used
 in the ordinal multivariate probit model of Rossi et al (2001). 
 This approach uses a quadratic parameterization of the cut-offs.
 The model is useful for modeling correlated ordinal data on a
 scale from 1, ..., k with different scale usage patterns.

 utilities

Covers many important models used
in marketing and micro-econometrics applications.
The package includes:
Bayes Regression (univariate or multivariate dep var),
Bayes Seemingly Unrelated Regression (SUR),
Binary and Ordinal Probit,
Multinomial Logit (MNL) and Multinomial Probit (MNP),
Multivariate Probit,
Negative Binomial (Poisson) Regression,
Multivariate Mixtures of Normals (including clustering),
Dirichlet Process Prior Density Estimation with normal base,
Hierarchical Linear Models with normal prior and covariates,
Hierarchical Linear Models with a mixture of normals prior and covariates,
Hierarchical Multinomial Logits with a mixture of normals prior
and covariates,
Hierarchical Multinomial Logits with a Dirichlet Process prior and covariates,
Hierarchical Negative Binomial Regression Models,
Bayesian analysis of choice-based conjoint data,
Bayesian treatment of linear instrumental variables models,
Analysis of Multivariate Ordinal survey data with scale
usage heterogeneity (as in Rossi et al, JASA (01)),
Bayesian Analysis of Aggregate Random Coefficient Logit Models as in BLP (see
Jiang, Manchanda, Rossi 2009)
For further reference, consult our book, Bayesian Statistics and
Marketing by Rossi, Allenby and McCulloch (Wiley 2005) and Bayesian Non- and Semi-Parametric
Methods and Applications (Princeton U Press 2014).

Peter Rossi

bayesm

Bayesian Inference for Marketing/Micro-Econometrics

cgetC function

This is a utility function which implements no error-checking.

cgetC: Obtain A List of Cut-offs for Scale Usage Problems

Description

Usage

Arguments

Value

Warning

References

See Also

Examples