dist_gran: compute distances and groups from algorithm based on raw...

In Sayani07/gracsr:

Description

compute distances and groups from algorithm based on raw distributions

Usage

dist_gran(
  .data,
  gran1 = NULL,
  gran2 = NULL,
  response = NULL,
  quantile_prob_val = seq(0.1, 0.9, 0.1)
)

Arguments

.data	a tsibble
gran1	one granularity e.g. hour_day, day_week, wknd_wday
gran2	one granularity distinct from gran1
response	measured variable
quantile_prob_val	values of probability for which distances between quantiles would be computed

Examples

library(gravitas)
library(tidyverse)
sm <- smart_meter10 %>%
  filter(customer_id %in% c("10006704", "10017936", "10006414", "10018250"))
gran1 <- "hour_day"
gran2 <- NULL
response <- "general_supply_kwh"
dist_gran(sm, "hour_day")
dist_gran(sm, "month_year")
sm %>%
  scale_gran(method = "robust") %>%
  dist_gran("hour_day")

Sayani07/gracsr documentation built on Dec. 18, 2021, 12:59 p.m.