univariate_forecast.Rdunivariate_forecast vector of responses and dataframe of predictors and automates
univariate_forecast(
response,
predictors,
model_type,
n_forecast = 10,
n_years_ahead = 1,
max_vars = 3
)A data frame of responses for the modeling (values to be forecast) containing a "time" column and "dev" column
A data frame of predictors used for forecasting recruitment
The type of model used to link predictors to forecasted recruitment. Can be "lm", "gam",
How many years to use as a holdout / test set
How many years ahead to forecast (defaults to 1) 1:n_vars variables, and then results are combined and sorted to remove duplicates
The maximum number of variables to include as predictors; defaults to 3
a list containing predictions, with elements
pred: the predictions
vars: the variable values used to fit the models
coefs: coefficient estimates from each year:iteration
response <- data.frame(time = 1:40, dev = rnorm(40))
predictors <- matrix(rnorm(400), ncol = 10)
#colnames(predictors) = paste0("X",1:ncol(predictors))
predictors <- as.data.frame(predictors)
predictors$time <- 1:40
lm_example <- univariate_forecast(response,
predictors,
model_type = "lm",
n_forecast = 10,
n_years_ahead = 1,
max_vars = 3)
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