predictlassoBinomial: Predict binomial outcomes from a fitted lassoBinomial_comm...

In nicholasjclark/BBS.occurrences: BBS community composition and co-occurrence analysis

Description

This function calculates linear predictors for species' binary observations using equations from a lassoBinomial_comm model.

lassoBinomial_metrics splits the data into ten folds and tests how well the lassoBinomial model predicts binary observations in each fold.

Matrices of predictive metrics are returned.

Usage

predictlassoBinomial(outcome_data, lassoBinomial, count_data, covariates,
  n_cores)

lassoBinomial_metrics(outcome_data, lassoBinomial, count_data, covariates,
  n_cores)

Arguments

outcome_data	dataframe. The input data to be predicted, where the columns represent binary occurrences of the species. Colnames from this sample dataset must exactly match the colnames in the dataset that was used to fit the lassoBinomial_comm
lassoBinomial	A fitted lassoBinomial_comm model object
count_data	A dataframe containing count observations for species (each column representing a different species)
covariates	A matrix of covariates, with nrow(covariates) == nrow(response)
n_cores	Positive integer stating the number of processing cores to split the job across. Default is parallel::detect_cores() - 1

Value

A matrix containing predictions for each observation in outcome_data.

nicholasjclark/BBS.occurrences documentation built on July 19, 2020, 8:31 p.m.