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determine optimal spatial data analysis scale

Source: R/loess_optscale.R
loess_optscale.Rd

Function for determining optimal spatial data analysis scale based on locally estimated scatter plot smoothing (LOESS) model.

Usage

loess_optscale(qvec, spscalevec, increase_rate = 0.05)

Arguments

qvec

A numeric vector of q statistics.

spscalevec

A numeric vector of spatial scales corresponding to qvec.

increase_rate

(optional) The critical increase rate of the number of discretization. Default is 5%.

Value

A numeric vector about optimal number of spatial scale and the critical increase rate of q value.

Author

Wenbo Lv lyu.geosocial@gmail.com

Examples

if (FALSE) { # \dontrun{
## The following code takes a long time to run:
library(tidyverse)
fvcpath = "https://github.com/SpatLyu/rdevdata/raw/main/FVC.tif"
fvc = terra::rast(paste0("/vsicurl/",fvcpath))
fvc1000 = fvc %>%
  terra::as.data.frame(na.rm = T) %>%
  as_tibble()
fvc5000 = fvc %>%
  terra::aggregate(fact = 5) %>%
  terra::as.data.frame(na.rm = T) %>%
  as_tibble()
qv1000 = factor_detector(fvc1000$fvc,
                         sdsfun::discretize_vector(fvc1000$premax,10,'quantile'))[[1]]
qv5000 = factor_detector(fvc5000$fvc,
                         sdsfun::discretize_vector(fvc5000$premax,10,'quantile'))[[1]]
loess_optscale(c(qv1000,qv5000),c(1000,5000))
} # }