simdata30nodes {envlpaster}R Documentation

A generated aster data set with 30 nodes


Simulated data for an aster analysis. Loads 7 objects.




The data frame with records for 3000 organisms over 10 years. The dataset corresponding to our aster analysis. The following four descriptions explain the elements of this dataset.


Indicates survival for each of the 10 years.


Counts offspring for each of the 10 years.


Indicates if w > 0 for each of the 10 years.


A covariate of potential interest, 10 in total.


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


The root data. For aster.default an nind by nnode matrix, for aster.formula an nind * nnode vector.


An nind by nnode by ncoef three-dimensional array, the model matrix. aster.formula constructs such a modmat from its formula, the data frame data, and the variables in the environment of the formula.


Necessary for changing to class aster.formula.


Necessary for changing to class aster.formula.


Necessary for changing to class aster.formula.


An object of class asterdata corresponding to simdata30nodes.


This object contains an aster data set in wide form, an object of class asterdata corresponding to the original data set, and vectors specifying the graphical structure of the aster model.

There are 3000 simulated individuals in this aster analysis. Our data is generated in two parts. The first part follows Technical report 671 (TR 671) on Charlie Geyer's Aster Models for Life History Analysis webpage. For our data, nind = 3000, ntime = 10, psurv = 0.95, prepr = 0.7, mpois = 1, and the seed is set at set.seed(13) which is different from the original simulation setup.

We follow the model construction in TR 671 through out6. We then generate a new dataset from the aster model where the components of the submodel mean-value parameter vector \tau corresponding to Darwinian fitness is in the space spanned by the first, second, and fourth eigenvectors of Fisher information.


Geyer, C. J. and Shaw, R. G. (2009). Model Selection in Estimation of Fitness Landscapes. Technical Report No. 671. School of Statistics, University of Minnesota.

[Package envlpaster version 0.1-2 Index]