suppressPackageStartupMessages(require(dplyr))
require(dplyr)
This document introduce you to piecewise basic usage. As an example, in this vignette the following piecewise model is build:
$$ f(x) = \Bigg{ \begin{array}{cc} x_1 + 2*x_2 & if & x_i \in [0:6) \ 20 - x_1 - x_2 & if & x_i \in [6:10] \ 0 & otherwise \end{array} $$
First, the three pieces of the model are generated.
# Models generation # First model generation mod_01 <- data.frame(x_1 = rep(1:6,each = 6), x_2 = rep(1:6, times = 6)) %>% mutate(y = x_1 + 2*x_2) %>% glm(formula = "y ~ x_1 + x_2", data = .) # Second model generation mod_02 <- data.frame(x_1 = rep(6:10,each = 5), x_2 = rep(6:10, times = 5)) %>% mutate(y = 20 - x_1 + x_2) %>% glm(formula = "y ~ x_1 + x_2", data = .) # Third model generation mod_03 <- data.frame(x_1 = 0, x_2 = 0, y = 0) %>% glm(formula = "y ~ x_1 + x_2", data = .)
Once the models have been created. The conditions of the model are defined
# Conditions generation # First condition cond_01 <- "x >= 0 & x < 6" # Second condition cond_02 <- "x >= 6 & x <= 10" # Third condition cond_03 <- "x < 0 & x > 10"
suppressPackageStartupMessages(require(piecewise)) p <- piecewise(models = list(mod_01, mod_02, mod_03), condition = c(cond_01, cond_02, cond_03))
require(piecewise) p <- piecewise(models = list(mod_01, mod_02, mod_03), condition = c(cond_01, cond_02, cond_03))
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