# IPModel: Estimates the pattern of internesting intervals for a set of... In phenology: Tools to Manage a Parametric Function that Describes Phenology and More

## Description

This function fits a model of internesting period.
The parameters are:

• `meanIP` : The average number of days between two nesting processes

• `DeltameanIP` : The shift in days for IP at each new clutch.

• `sdIP` : The standard deviation of number of days between two nesting processes

• `minIP` : The minimum number of days between two nesting processes

• `pAbort` : The -logit of the probability to abort a nesting process

• `meanAbort` : The average of the number of days after the abortion of a nesting process

• `sdAbort` : The standard deviation of the number of days after the abortion of a nesting process

• `pCapture` : The -logit of the probability to capture a female on the beach

• `meanECF` : The average number of clutch a female will try to do being reprensented as ECF

• `sdECF` : The standard deviation of number of clutch a female will try to do

• `N` : The number of replicates to generate the distribution (default is 10000 if not indicated)

• `ECF.x` : The relative proportion of females nesting with ECF = x (ECF.1 being fixed to 1)

## Usage

 ```1 2 3 4 5 6``` ```IPModel( par, parallel = TRUE, limits = list(meanIP = 40, meanECF = 4, minIP = 15, sdAbort = 1, sdIP = 1, sdECF = 1, DeltameanIP = 0.5, maxDays = 365) ) ```

## Arguments

 `par` Set of parameters `parallel` If TRUE, will use parallel computing `limits` A list of limits for various parameters

## Details

IPModel estimates the pattern of internesting intervals for a set of parameters.

## Value

Return a list with two elements.

## Author(s)

Marc Girondot

Other Model of Internesting Period: `IPFit()`, `IPPredict()`, `plot.IP()`, `summary.IP()`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```## Not run: library(phenology) # Example par <- c(meanIP = 9.8, sdIP = 0.1, minIP = 7, pAbort = -logit(0.1), meanAbort = 2, sdAbort = 0.05, pCapture = -logit(0.8), meanECF = 4, sdECF = 0.1) model <- IPModel(c(par, N=10000)) plot(model) ## End(Not run) ```