From: Bayesian Models for Astrophysical Data, Cambridge Univ. Press

(c) 2017,  Joseph M. Hilbe, Rafael S. de Souza and Emille E. O. Ishida  

 

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Code 6.1 Synthetic data following a Poisson distribution in R

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set.seed(2016)
nobs <- 500


x <- runif(nobs)
xb <- 1 + 2*x
py <- rpois(nobs, exp(xb))
summary(myp <- glm(py ~ x, family=poisson))

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Output on screen:

Call:

glm(formula = py ~ x, family = poisson)

 

Deviance Residuals:

      Min             1Q      Median            3Q          Max

-3.2419      -0.7687      -0.0162      0.6284      3.1752

 

Coefficients:

                          Estimate       Std. Error        z value      Pr(>|z|)

(Intercept)          1.00106          0.04037           24.80      <2e-16 ***

x                         2.02577          0.05728           35.37      <2e-16 ***

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Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

 

(Dispersion parameter for poisson family taken to be 1)

 

       Null deviance: 1910.87 on 499 degrees of freedom

Residual deviance:   540.07 on 498 degrees of freedom

AIC: 2428.8

 

Number of Fisher Scoring iterations: 4