compute_norm_pairwise_max: Title Compute normalised maximum pairwise distances

In Sayani07/gravitas: Explore Probability Distributions for Bivariate Temporal Granularities

Title Compute normalised maximum pairwise distances

Description

Title Compute normalised maximum pairwise distances

Usage

compute_norm_pairwise_max(
  .data,
  gran_x = NULL,
  gran_facet = NULL,
  response = NULL,
  quantile_prob = seq(0.01, 0.99, 0.01),
  dist_ordered = TRUE,
  nperm = 100,
  lambda = 0.67
)

Arguments

.data	data for which mmpd needs to be calculated
gran_x	granularities mapped across x levels
gran_facet	granularities mapped across facetss
response	univarite response variable
quantile_prob	probabilities
dist_ordered	if categories are ordered
nperm	number of permutations required for normalisation
lambda	value of the tuning parameter for computing weighted pairwise distances

Value

the weighted pairwise distance normalised using permutation

Examples

library(dplyr)
library(parallel)
sm <- smart_meter10 %>%
  filter(customer_id %in% c("10017936"))
gran_x <- "week_month"
gran_facet <- "week_fortnight"
v <- compute_norm_pairwise_max(sm, gran_x, gran_facet,
  response = general_supply_kwh, nperm = 10
)
# month of the year not working in this setup

Sayani07/gravitas documentation built on June 18, 2022, 2:40 a.m.