aster (version 1.1-3)

sim: Simulated Life History Data

Description

Data on life history traits for four years and five fitness components

Usage

data(sim)

Format

Loads nine objects. The objects beta.true, mu.true, phi.true, and theta.true are the simulation truth parameter values in different parametrizations.

beta.true

Regression coefficient vector for model resp ~ varb + 0 + z1 + z2 + I(z1^2) + I(z1*z2) + I(z2^2).

mu.true

Unconditional mean value parameter vector for same model.

phi.true

Unconditional canonical value parameter vector for same model.

theta.true

Conditional canonical value parameter vector for same model.

The objects fam, pred, and vars specify the aster model graphical and probabilistic structure.

fam

Integer vector giving the families of the variables in the graph.

pred

Integer vector giving the predecessors of the variables in the graph.

vars

Character vector giving the names of the variables in the graph.

The objects ladata and redata are the simulated data in two forms "wide" and "long" in the terminology of the reshape function.

ladata

Data frame with variables y, z1, z2 used for Lande-Arnold type estimation of fitness landscape. y is the response, fitness, and z1 and z1 are predictor variables, phenotypes.

redata

Data frame with variables resp, z1, z2, varb, id, root used for aster type estimation of fitness landscape. resp is the response, containing all components of fitness, and z1 and z1 are predictor variables, phenotypes. varb is a factor whose levels are are elements of vars indicating which elements of resp go with which nodes of the aster model graphical structure. The variables z1 and z2 have been set equal to zero except when grep("nseed", varb) is TRUE. For the rationale see Section 3.2 of TR 669 referenced below.

References

Geyer, C. J and Shaw, R. G. (2009) Hypothesis Tests and Confidence Intervals Involving Fitness Landscapes fit by Aster Models. Technical Report No. 671. School of Statistics, University of Minnesota. http://hdl.handle.net/11299/56219.

Examples

data(sim)
if (FALSE) {
### CRAN policy says examples must take < 5 sec.  This doesn't.
out6 <- aster(resp ~ varb + 0 + z1 + z2 + I(z1^2) + I(z1*z2) + I(z2^2),
    pred, fam, varb, id, root, data = redata)
summary(out6)
}
lout <- lm(y ~ z1 + z2 + I(z1^2) + I(z1*z2) + I(z2^2), data = ladata)
summary(lout)