Fit a Sigmoidal Model to Data.

This function fits a sigmoidal model (Pearl, Gompertz, or Logistic) to the provided data.

Usage

fit_sigmoidal(data, x_col, y_col, model_type)

Arguments

data

A data frame containing the time (x_col) and completion (y_col) vectors.

x_col

The name of the time vector.

y_col

The name of the completion vector.

model_type

The name of the sigmoidal model (Pearl, Gompertz, or Logistic).

Value

The function returns a list of results for the sigmoidal model.

Examples

# Set up a data frame of time and completion percentage data
data <- data.frame(time = 1:10, completion = c(5, 15, 40, 60, 70, 75, 80, 85, 90, 95))

# Fit a logistic model to the data.
fit <- fit_sigmoidal(data, "time", "completion", "logistic")

# Use the model to predict future completion times.
predictions <- predict_sigmoidal(fit, seq(min(data$time), max(data$time),
  length.out = 100
), "logistic")

# Predict with 95% confidence bounds
predictions_ci <- predict_sigmoidal(fit, seq(min(data$time), max(data$time),
  length.out = 100
), "logistic", conf_level = 0.95)