dPois: Mixture two Poisson Regression Models

In tlemix: Trimmed Maximum Likelihood Estimation

Description

In this data set we consider two Poisson regression models with equal mixing proportions and with additional noise. For each Poisson regression model 100 data points are generated according to a Poisson distribution. For the noise we generated 50 points from a uniform distribution over the range of each variate.

Usage

data(dPois)

Format

A data frame with 150 observations on the following 3 variables.

y

A numeric vector of y-coordinates

x

A numeric vector of x-coordinates

Author(s)

P. Neytchev, P. Filzmoser, R. Patnaik, A. Eisl and R. Boubela, <[e-mail]> http://www.statistik.tuwien.ac.at/public/filz/

See Also

TLE

Examples

data(dPois)
str(dPois)
# Example needs some computing time:
# est.tle <- TLE(y~x,"poisson",data=dPois,Density=flexmix.Density,
#            Estimate=flexmix.Estimate,msglvl=1,nc=2,kTrim=200,class="hard")
# tleplot(est.tle,dPois)

Example output

'data.frame':	250 obs. of  2 variables:
 $ y: num  12 29 38 9 18 58 37 50 28 11 ...
 $ x: num  69 -13 -78 91 13 -139 -92 -118 -57 74 ...

tlemix documentation built on May 2, 2019, 5:57 a.m.