dist_wpd: Title Compute distances based on wpd Computes distances...

In Sayani07/gracsr:

Description

Title Compute distances based on wpd Computes distances between subjects based on wpd across different granularities

Usage

dist_wpd(.data, harmony_tbl = NULL, response = NULL, nperm = 100)

Arguments

.data	a tsibble
harmony_tbl	a harmony table
response	measured variable
nperm	number of permutations for normalization

Value

returns an object of class "dist"

Examples

library(gravitas)
library(tidyverse)
library(parallel)
library(tsibble)
library(rlang)
sm <- smart_meter10 %>%
  filter(customer_id %in% c("10006704", "10017936", "10006414", "10018250"))
gran1 <- "hour_day"
gran2 <- NULL
harmonies <- sm %>%
  harmony(
    ugran = "year",
    filter_in = "wknd_wday",
    filter_out = c("hhour", "fortnight", "quarter", "semester")
  )
harmonies1 <- harmonies %>% mutate(facet_variable = NA)

h <- harmonies1 %>%
  select(-facet_levels) %>%
  distinct() %>%
  mutate(facet_levels = NA) %>%
  filter(x_variable %in% c("month_year", "hour_day", "wknd_wday"))

v <- dist_wpd(sm, harmony_tbl = h)
v

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