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R
OpenMx

mxMarginalPoisson

Indicator with marginal Poisson distribution

Description

Indicator with marginal Poisson distribution

Usage

mxMarginalPoisson(
  vars,
  maxCount = NA,
  lambda,
  zeroInf = 0.01,
  free = TRUE,
  labels = NA,
  lbound = 0,
  ubound = c(1, NA)
)

Arguments

vars

character vector of manifest indicators
maxCount

maximum observed count
lambda

non-negative means
zeroInf

zero inflation parameter in probability units
free

logical vector indicating whether paremeters are free
labels

character vector of parameter labels
lbound

numeric vector of lower bounds
ubound

numeric vector of upper bounds

Value

a list of MxMarginPoisson obects

OpenMx

Extended Structural Equation Modelling

v2.19.5
Apache License (== 2.0)
Authors
Steven M. Boker [aut], Michael C. Neale [aut], Hermine H. Maes [aut], Michael J. Wilde [ctb], Michael Spiegel [aut], Timothy R. Brick [aut], Ryne Estabrook [aut], Timothy C. Bates [aut], Paras Mehta [ctb], Timo von Oertzen [ctb], Ross J. Gore [aut], Michael D. Hunter [aut], Daniel C. Hackett [ctb], Julian Karch [ctb], Andreas M. Brandmaier [ctb], Joshua N. Pritikin [aut, cre], Mahsa Zahery [aut], Robert M. Kirkpatrick [aut], Yang Wang [ctb], Ben Goodrich [ctb], Charles Driver [ctb], Massachusetts Institute of Technology [cph], S. G. Johnson [cph], Association for Computing Machinery [cph], Dieter Kraft [cph], Stefan Wilhelm [cph], Sarah Medland [cph], Carl F. Falk [cph], Matt Keller [cph], Manjunath B G [cph], The Regents of the University of California [cph], Lester Ingber [cph], Wong Shao Voon [cph], Juan Palacios [cph], Jiang Yang [cph], Gael Guennebaud [cph], Jitse Niesen [cph]
Initial release
2021-03-26

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