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Last data update: 2014.03.03

R: Function to build growth objects

makeGrowthObj

R Documentation

Function to build growth objects

Description

A function that fits regressions that define growth (following next size, size increment, or log size increment) and from these build growth objects for which methods to build an IPM object are defined; alternatively, the function creates growth objects following a specified formula with specified coefficients and sd.

Usage

makeGrowthObj(dataf=NULL, Formula = sizeNext ~ size, 
	regType = "constantVar", Family = "gaussian", link = NULL, coeff=NULL,sd=NULL)

Arguments

`dataf`	a dataframe with columns ‘size’ and ‘sizeNext’(‘size’ is size at t, ‘sizeNext’ is size at t+1); facultatively, dataf may include ‘covariate’ and ‘covariatel’ for a single discrete covariate, indicating values at t, and at t+1, respectively; these must take values of sequential integers, starting at ‘1’. For models fitting growth increment, 'incr' or 'logincr' may be directly provided as a column in the dataframe, otherwise they are calculated as dataf$sizeNext - dataf$size or log(dataf$sizeNext - dataf$size), respectively.
`Formula`	a formula describing the desired explanatory variables (interactions, etc) according to the R notation for `formula`. style, i.e. separated by ‘+’, ‘*’, ‘:’ and response variable. Possible covariates include ‘size’, 'size2' (size^2), ‘size3’ (size^3),‘logsize’ (log(size)), ‘logsize2’ (log(size)^2), and ‘covariate’ (if this name is used, the assumption is made that this is a discrete covariate from which compound matrices may be constructed); or any other covariate available in dataf.
`regType`	possible values include ‘constantVar’ or ‘changingVar’
`Family`	possible values include ‘gaussian’, ‘poisson’, ‘negbin’
`link`	defaults to NULL, currently only relevant with Family="negbin", and only "log" and "identity" are permitted
`coeff`	numeric vector of required coefficients to be imposed if dataf is NULL; must be compatible with Formula
`sd`	numeric of required sd to be imposed if dataf is NULL

Value

An object of class growthObj, or growthObjPois, growthObjIncr, or growthObjLogIncr; or growthObjDeclineVar, or growthObjIncrDeclineVar, or growthObjLogIncrDeclineVar. These are S4 objects which contain the slots:

fit

an object of class lm or glm or gls that can be used with predict in the growth methods

Slots can be listed by using slotNames(growthObj)

Note

See manual for details on building case-specific growth objects. Note that DeclineVar objects cannot currently be constructed without a data-frame.

Author(s)

C. Jessica E. Metcalf, Sean M. McMahon, Roberto Salguero-Gomez & Eelke Jongejans

Examples

#generate data
dff <- generateData()
#make simple linear regression growth object relating size to size at t+1
(gr1 <- makeGrowthObj(dataf = dff, Formula = sizeNext~size))
#same but relating size to incr
(gr1 <- makeGrowthObj(dataf = dff, Formula = incr ~ size))

#assess fit 
picGrow(dff,gr1)

#same but relating size to incr and discrete covariate
(gr1 <- makeGrowthObj(dataf = dff, Formula = incr ~ size + covariate, 
	regType = "changingVar"))
#with declining increment
(gr1 <- makeGrowthObj(dataf = dff, Formula = incr ~ size + covariate, 
	regType = "changingVar"))

#now specifying parameters and supplying no data
gr1 <- makeGrowthObj(Formula = incr ~ size + covariate,coeff=c(1,1,1),sd=1)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(IPMpack)
Loading required package: Matrix
Loading required package: MASS
Loading required package: nlme
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/IPMpack/makeGrowthObj.Rd_%03d_medium.png", width=480, height=480)
> ### Name: makeGrowthObj
> ### Title: Function to build growth objects
> ### Aliases: makeGrowthObj
> 
> ### ** Examples
> 
> #generate data
> dff <- generateData()
> #make simple linear regression growth object relating size to size at t+1
> (gr1 <- makeGrowthObj(dataf = dff, Formula = sizeNext~size))
An object of class "growthObj"
Slot "fit":

Call:
lm(formula = Formula, data = dataf)

Coefficients:
(Intercept)         size  
     0.2987       0.7868  


Slot "sd":
[1] 1.059566

> #same but relating size to incr
> (gr1 <- makeGrowthObj(dataf = dff, Formula = incr ~ size))
[1] "building incr as sizeNext - size"
An object of class "growthObjIncr"
Slot "fit":

Call:
lm(formula = Formula, data = dataf)

Coefficients:
(Intercept)         size  
     0.2987      -0.2132  


Slot "sd":
[1] 1.059566

> 
> #assess fit 
> picGrow(dff,gr1)
> 
> #same but relating size to incr and discrete covariate
> (gr1 <- makeGrowthObj(dataf = dff, Formula = incr ~ size + covariate, 
+ 	regType = "changingVar"))
[1] "building incr as sizeNext - size"
An object of class "growthObjIncrDeclineVar"
Slot "fit":
$coefficients
(Intercept)        size  covariate2 
  0.8180437  -0.2103019  -0.6496811 

$sigmax2
[1] 0.921458

$var.exp.coef
[1] -0.08690733

$fit
Generalized least squares fit by REML
  Model: Formula 
  Data: dataf 
  Log-restricted-likelihood: -634.7458

Coefficients:
(Intercept)        size  covariate2 
  0.8180437  -0.2103019  -0.6496811 

Variance function:
 Structure: Exponential of variance covariate
 Formula: ~fitted(.) 
 Parameter estimates:
      expon 
-0.08690733 
Degrees of freedom: 435 total; 432 residual
Residual standard error: 0.959926 


> #with declining increment
> (gr1 <- makeGrowthObj(dataf = dff, Formula = incr ~ size + covariate, 
+ 	regType = "changingVar"))
[1] "building incr as sizeNext - size"
An object of class "growthObjIncrDeclineVar"
Slot "fit":
$coefficients
(Intercept)        size  covariate2 
  0.8180437  -0.2103019  -0.6496811 

$sigmax2
[1] 0.921458

$var.exp.coef
[1] -0.08690733

$fit
Generalized least squares fit by REML
  Model: Formula 
  Data: dataf 
  Log-restricted-likelihood: -634.7458

Coefficients:
(Intercept)        size  covariate2 
  0.8180437  -0.2103019  -0.6496811 

Variance function:
 Structure: Exponential of variance covariate
 Formula: ~fitted(.) 
 Parameter estimates:
      expon 
-0.08690733 
Degrees of freedom: 435 total; 432 residual
Residual standard error: 0.959926 


> 
> #now specifying parameters and supplying no data
> gr1 <- makeGrowthObj(Formula = incr ~ size + covariate,coeff=c(1,1,1),sd=1)
> 
> 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>