Progress model prediction

Calculate the predicted values of a model. The object, provided needs to have already passed from fit, in order to include a model slot.

Usage

predict(object, ...)

# S4 method for ProgressModelList
predict(object, pdata)

# S4 method for ProgressBM
predict(object, pdata)

# S4 method for ProgressBMM
predict(object, pdata)

# S4 method for ProgressCLM
predict(object, pdata)

# S4 method for ProgressCLMM
predict(object, pdata)

# S4 method for ProgressSRF
predict(object, pdata)

# S4 method for ProgressMRF
predict(object, pdata)

Arguments

object

an object of class ProgressModel or ProgressModelList.

...

extra arguments.

pdata

data.frame. The data used in model prediction.

Value

data.frame.

Examples

if (FALSE) {
# Create a Region object
library(cronus)
region <- Region(name = "nebraska", type = "us state",
                 div = c(country = "United States", state = "Nebraska"))

# Create a model
object1 <- new("ProgressBM",
               region = region,
               crop = "Corn",
               data = data_progress$Corn,
               formula = "CumPercentage ~ Time + agdd") # ProgressModel

# Create another model
object2 <- new("ProgressCLM",
               region = region,
               crop = "Soybeans",
               data = data_progress$Soybeans,
               formula = "Stage ~ Time + agdd + adayl") # ProgressModel

# Concatenate the models
object <- c(object1, object2) # ProgressModelList

# Fit
object <- fit(object)

# Plot
plot(object, cumulative = TRUE, seasons = 2002)

# Predict
predict(object, data_progress)

# Evaluate
object <- evaluate(object, maxsam = 100, seed = 1)
plot_metrics(object)

# Summarize
summary(object)

# Report
report(object, name = "example_report", path = getwd())
}