Could you clarify what are the parameters and why it’s formulated that way?
-Matti
> On 22 Mar 2016, at 14:17, Thierry Onkelinx <thierry.onkel...@inbo.be> wrote:
>
> Dear Matti,
>
> What about this?
>
> dzeroinflpois <- function(x, lambda, zero){
> ifelse(x == 0, zero, 0) + dpois(x, lambda) / (1 - zero)
> }
> plot(x, dzeroinflpois(x, lambda = 10, zero = 0.2), type = "l")
>
>
>
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
> Forest
> team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
> Kliniekstraat 25
> 1070 Anderlecht
> Belgium
>
> To call in the statistician after the experiment is done may be no more than
> asking him to perform a post-mortem examination: he may be able to say what
> the experiment died of. ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data. ~ Roger Brinner
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of data. ~
> John Tukey
>
> 2016-03-22 13:04 GMT+01:00 Matti Viljamaa <mvilja...@kapsi.fi
> <mailto:mvilja...@kapsi.fi>>:
> I’m doing some optimisation that I first did with normal Poisson (only
> parameter theta was estimated), but now I’m doing the same with a
> zero-inflated Poisson model which
> gives me two estimated parameters theta and p (p is also pi in some notation).
>
> My question is, is there something equivalent to dpois that would use both of
> the parameters (or is the p parameter possibly unnecessary)?
>
> I’m calculating the “fit” of the Poisson model
>
> i.e. like
>
> x = c(0,1,2,3,4,5,6)
> y = c(3062,587,284,103,33,4,2)
> fit1 <- sum(y)*dpois(x, est_theta)
>
> and then comparing fit1 to the real observations.
> [[alternative HTML version deleted]]
>
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