configzeliggui_0.xml

<?xml version="1.0" encoding="UTF-8"?>
<zelig xmlns="http://gking.harvard.edu/zelig" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://gking.harvard.edu/zelig http://thedata.org/files/thedata/schema/ZeligInterfaceDefinition_1_1.xsd">
<model name="aov" label="Models for Continuous Dependent Variables">
<description>Fit an Analysis of Variance Model</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/aov.pdf"/>
<packageDependency name= "stats" version= "2.5.0"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="cloglog.net" label="Models for Dichotomous Dependent Variables">
<description>Social Network Complementary Log Log Regression for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/cloglog.net.pdf"/>
<packageDependency name= "sna" version= "1.4"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="pi">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="coxph" label="Models for Continous Bounded Dependent Variables" specialFunction="Surv">
<description>Cox Proportional Hazard Regression for Duration Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/coxph.pdf"/>
<packageDependency name= "survival" version= "2.34"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome maxVar="2" minVar="2" >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="ei.dynamic" label="Ecological Inference Models" specialFunction="cbind">
<description>Quinn's Dynamic Ecological Inference Model</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/ei.dynamic.pdf"/>
<packageDependency name= "MCMCpack" version= "0.8-2"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome minVar="2" >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="ei.hier" label="Ecological Inference Models" specialFunction="cbind">
<description>Hierarchical Ecological Inference Model for  2 x 2 Tables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/ei.hier.pdf"/>
<packageDependency name= "MCMCpack" version= "0.8-2"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome minVar="2" >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="ei.RxC" label="Ecological Inference Models" specialFunction="cbind">
<description>Hierarchical Multinomial-Dirichlet Ecological Inference Model for R x C Tables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/ei.RxC.pdf"/>
<packageDependency name= "stats" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome minVar="2" >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="exp" label="Models for Continous Bounded Dependent Variables" specialFunction="Surv">
<description>Exponential Regression for Duration Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/exp.pdf"/>
<packageDependency name= "survival" version= "2.0"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
 <outcome minVar="1" maxVar="1" label="Duration">
<modelingType>continuous</modelingType>
</outcome>
<outcome maxVar="1" minVar="0" label="Censored">
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="factor.bayes" label="Models for Continuous Dependent Variables" specialFunction="cbind">
<description>Bayesian Factor Analysis</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/factor.bayes.pdf"/>
<packageDependency name= "MCMCpack" version= "0.6"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome minVar="3" >
<modelingType>continuous</modelingType>
</outcome>
</equation>
</formula>
<setx maxSetx="0"/>
 </model>
<model name="factor.mix" label="Models for Mixed Dependent Variables" specialFunction="cbind">
<description>Mixed Data Factor Analysis</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/factor.mix.pdf"/>
<packageDependency name= "MCMCpack" version= "0.6"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome minVar="2" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</outcome>
</equation>
</formula>
<setx maxSetx="0"/>
 </model>
<model name="factor.ord" label="Models for Ordinal Dependent Variables" specialFunction="cbind">
<description>Ordinal Data Factor Analysis</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/factor.ord.pdf"/>
<packageDependency name= "MCMCpack" version= "0.6"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome minVar="2" >
<modelingType>ordinal</modelingType>
</outcome>
</equation>
</formula>
<setx maxSetx="0"/>
 </model>
<model name="gamma" label="Models for Continous Bounded Dependent Variables">
<description>Gamma Regression for Continuous, Positive Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/gamma.pdf"/>
<packageDependency name= "stats" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="lambda">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="gamma.gee" label="Models for Continous Bounded Dependent Variables">
<description>General Estimating Equation for Gamma Regression</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/gamma.gee.pdf"/>
<packageDependency name= "gee" version= "4.13-12"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="lambda">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="gamma.net" label="Models for Continous Bounded Dependent Variables">
<description>Social Network Gamma Regression for Continuous, Positive Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/gamma.net.pdf"/>
<packageDependency name= "sna" version= "1.4"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="lambda">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="gamma.survey" label="Models for Continous Bounded Dependent Variables">
<description>Survey-Weighted Gamma Regression for Continuous, Positive Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/gamma.survey.pdf"/>
<packageDependency name= "survey" version= "3.6-13"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="lambda">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="irt1d" label="Models for Dichotomous Dependent Variables" specialFunction="cbind">
<description>One Dimensional Item Response Model</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/irt1d.pdf"/>
<packageDependency name= "MCMCpack" version= "0.6"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="pi">
<outcome minVar="1" >
<modelingType>binary</modelingType>
</outcome>
</equation>
</formula>
<setx maxSetx="0"/>
 </model>
<model name="logit" label="Models for Dichotomous Dependent Variables">
<description>Logistic Regression for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/logit.pdf"/>
<packageDependency name= "stats" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="pi">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="logit.bayes" label="Models for Dichotomous Dependent Variables">
<description>Bayesian Logistic Regression for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/logit.bayes.pdf"/>
<packageDependency name= "MCMCpack" version= "0.6"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="pi">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="logit.gam" label="Models for Dichotomous Dependent Variables">
<description>Generalized Additive Model for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/logit.gam.pdf"/>
<packageDependency name= "mgcv" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="pi">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="logit.gee" label="Models for Dichotomous Dependent Variables">
<description>General Estimating Equation for Logistic Regression</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/logit.gee.pdf"/>
<packageDependency name= "gee" version= "4.13-12"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="pi">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="logit.net" label="Models for Dichotomous Dependent Variables">
<description>Social Network Logistic Regression for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/logit.net.pdf"/>
<packageDependency name= "sna" version= "1.4"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="pi">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="logit.survey" label="Models for Dichotomous Dependent Variables">
<description>Survey-Weighted Logistic Regression for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/logit.survey.pdf"/>
<packageDependency name= "survey" version= "3.6-13"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="pi">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="lognorm" label="Models for Continous Bounded Dependent Variables" specialFunction="Surv">
<description>Log-Normal Regression for Duration Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/lognorm.pdf"/>
<packageDependency name= "survival" version= "2.2"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
 <outcome minVar="1" maxVar="1" label="Duration">
<modelingType>continuous</modelingType>
</outcome>
<outcome maxVar="1" minVar="0" label="Censored">
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="ls" label="Models for Continuous Dependent Variables">
<description>Least Squares Regression for Continuous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/ls.pdf"/>
<packageDependency name= "stats" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="ls.net" label="Models for Continuous Dependent Variables">
<description>Social Network Least Squares Regression for Continuous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/ls.net.pdf"/>
<packageDependency name= "sna" version= "1.4"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="mlogit.bayes" label="Multinomial Choice Models" specialFunction="as.factor">
<description>Bayesian Multinomial Logistic Regression for Dependent Variables with Unordered Categorical Values</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/mlogit.bayes.pdf"/>
<packageDependency name= "MCMCpack" version= "0.6"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome maxVar="1" minVar="1" >
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="mloglm" label="Multinomial Choice Models">
<description>Multinomial Log-Linear Regression for Contingency Table Models</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/mloglm.pdf"/>
<packageDependency name= "nnet" version= "0.6"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="negbin" label="Event Count Models">
<description>Negative Binomial Regression for Event Count Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/negbin.pdf"/>
<packageDependency name= "MASS" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>discrete</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="normal.gam" label="Models for Continuous Dependent Variables">
<description>Generalized Additive Model for Continuous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/normal.gam.pdf"/>
<packageDependency name= "mgcv" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="normal.gee" label="Models for Continuous Dependent Variables">
<description>General Estimating Equation for Normal Regression</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/normal.gee.pdf"/>
<packageDependency name= "gee" version= "4.13-12"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="normal.net" label="Models for Continuous Dependent Variables">
<description>Social Network Normal Regression for Continuous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/normal.net.pdf"/>
<packageDependency name= "sna" version= "1.4"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="normal.survey" label="Models for Continuous Dependent Variables">
<description>Survey-Weighted Normal Regression for Continuous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/normal.survey.pdf"/>
<packageDependency name= "survey" version= "3.6-13"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="ologit" label="Models for Ordinal Dependent Variables" specialFunction="as.factor">
<description>Ordinal Logistic Regression for Ordered Categorical Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/ologit.pdf"/>
<packageDependency name= "MASS" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome maxVar="1" minVar="1" >
<modelingType>ordinal</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="oprobit" label="Models for Ordinal Dependent Variables" specialFunction="as.factor">
<description>Ordinal Probit Regression for Ordered Categorical Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/oprobit.pdf"/>
<packageDependency name= "MASS" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome maxVar="1" minVar="1" >
<modelingType>ordinal</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="oprobit.bayes" label="Models for Ordinal Dependent Variables" specialFunction="as.factor">
<description>Bayesian Ordered Probit Regression</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/oprobit.bayes.pdf"/>
<packageDependency name= "MCMCpack" version= "0.6"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome maxVar="1" minVar="1" >
<modelingType>ordinal</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="poisson" label="Event Count Models">
<description>Poisson Regression for Event Count Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/poisson.pdf"/>
<packageDependency name= "stats" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="lambda">
<outcome >
<modelingType>discrete</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="poisson.bayes" label="Event Count Models">
<description>Bayesian Poisson Regression</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/poisson.bayes.pdf"/>
<packageDependency name= "MCMCpack" version= "0.6"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="lambda">
<outcome >
<modelingType>discrete</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="poisson.gam" label="Event Count Models">
<description>Generalized Additive Model for Event Count Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/poisson.gam.pdf"/>
<packageDependency name= "mgcv" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="lambda">
<outcome >
<modelingType>discrete</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="poisson.gee" label="Event Count Models">
<description>General Estimating Equation for Poisson Regression</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/poisson.gee.pdf"/>
<packageDependency name= "gee" version= "4.13-12"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="lambda">
<outcome >
<modelingType>discrete</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="poisson.net" label="Event Count Models">
<description>Social Network Poisson Regression for Event Count Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/poisson.net.pdf"/>
<packageDependency name= "sna" version= "1.4"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="lambda">
<outcome >
<modelingType>discrete</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="poisson.survey" label="Event Count Models">
<description>Survey-Weighted Poisson Regression for Event Count Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/poisson.survey.pdf"/>
<packageDependency name= "survey" version= "3.6-13"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="lambda">
<outcome >
<modelingType>discrete</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="probit" label="Models for Dichotomous Dependent Variables">
<description>Probit Regression for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/probit.pdf"/>
<packageDependency name= "stats" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="probit.bayes" label="Models for Dichotomous Dependent Variables">
<description>Bayesian Probit Regression for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/probit.bayes.pdf"/>
<packageDependency name= "MCMCpack" version= "0.6"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="probit.gam" label="Models for Dichotomous Dependent Variables">
<description>Generalized Additive Model for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/probit.gam.pdf"/>
<packageDependency name= "mgcv" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="probit.gee" label="Models for Dichotomous Dependent Variables">
<description>General Estimating Equation for Probit Regression</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/probit.gee.pdf"/>
<packageDependency name= "gee" version= "4.13-12"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="pi">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="probit.net" label="Models for Dichotomous Dependent Variables">
<description>Social Network Probit Regression for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/probit.net.pdf"/>
<packageDependency name= "stats" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="probit.survey" label="Models for Dichotomous Dependent Variables">
<description>Survey-Weighted Probit Regression for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/probit.survey.pdf"/>
<packageDependency name= "survey" version= "3.6-13"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="relogit" label="Models for Dichotomous Dependent Variables">
<description>Rare Events Logistic Regression for Dichotomous Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/relogit.pdf"/>
<packageDependency name= "stats" version= "0.1"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="pi">
<outcome >
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="tobit" label="Models for Continuous Dependent Variables">
<description>Linear regression for Left-Censored Dependent Variable</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/tobit.pdf"/>
<packageDependency name= "survival" version= "2.2"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="tobit.bayes" label="Models for Continuous Dependent Variables">
<description>Bayesian Linear Regression for a Censored Dependent Variable</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/tobit.bayes.pdf"/>
<packageDependency name= "MCMCpack" version= "0.6"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="mu">
<outcome >
<modelingType>continuous</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>
<model name="weibull" label="Models for Continous Bounded Dependent Variables" specialFunction="Surv">
<description>Weibull Regression for Duration Dependent Variables</description>
<helpLink url="http://gking.harvard.edu/zelig/doc/weibull.pdf"/>
<packageDependency name= "survival" version= "2.2"/>
<formula minEquations="1" maxEquations="1" simulEq="0">
<equation name="lambda">
 <outcome minVar="1" maxVar="1" label="Duration">
<modelingType>continuous</modelingType>
</outcome>
<outcome maxVar="1" minVar="0" label="Censored">
<modelingType>binary</modelingType>
</outcome>
 <explanatory  minVar="1" >
<modelingType>continuous</modelingType>
<modelingType>discrete</modelingType>
<modelingType>nominal</modelingType>
<modelingType>ordinal</modelingType>
<modelingType>binary</modelingType>
</explanatory>
</equation>
</formula>
<setx maxSetx="2"/>
 </model>

</zelig>