emp_spatial_cov: Computes empirical spatial covariance using a dataframe or a...

In stxplore: Exploration of Spatio-Temporal Data

Computes empirical spatial covariance using a dataframe or a stars object

Description

Computes empirical spatial covariance by removing trends and examining residuals. It can compute lag-0 or log-1 empirical covariance either by latitude or longitude. You can split up the spatial domain by latitude or longitude and plot the covariance for each longitudinal/latitudinal strips.

Usage

emp_spatial_cov(
  x,
  lat_or_lon_strips = "lon",
  quadratic_time = FALSE,
  quadratic_space = FALSE,
  num_strips = 1,
  lag = 0,
  ...
)

## S3 method for class 'data.frame'
emp_spatial_cov(
  x,
  lat_or_lon_strips = "lon",
  quadratic_time = FALSE,
  quadratic_space = FALSE,
  num_strips = 1,
  lag = 0,
  lat_col,
  lon_col,
  t_col,
  z_col,
  ...
)

## S3 method for class 'stars'
emp_spatial_cov(
  x,
  lat_or_lon_strips = "lon",
  quadratic_time = FALSE,
  quadratic_space = FALSE,
  num_strips = 1,
  lag = 0,
  ...
)

## S3 method for class 'spatialcov'
autoplot(object, xlab = "Latitude", ...)

Arguments

x	A stars object or a dataframe. Arguments differ according to the input type.
lat_or_lon_strips	Takes the values lat or lon. The value lat produces latitudinal strips, i.e., covariance plots over longitude for different latitudinal strips. The value lon produces longitudinal strips, i.e., covariance plots over latitude for different longitudinal strips.
quadratic_time	If TRUE a linear model with quadratic time is fitted and residuals computed. If FALSE the model is fitted with linear space and time coefficients.
quadratic_space	If TRUE a linear model with quadratic space is fitted and residuals computed. If FALSE the model is fitted with linear space and time coefficients.
num_strips	The number of latitudinal/longitudinal strips to produce. This is used when plotting using autoplot.
lag	Lag can be either 0 or 1.
...	Other arguments currently ignored.
lat_col	For dataframes: the column or the column name giving the latitude. The y coordinate can be used instead of latitude.
lon_col	For dataframes: the column or the column name giving the longitude. The x coordinate can be used instead of longitude.
t_col	For dataframes: the time column. Time must be a set of discrete integer values.
z_col	For dataframes: the The quantity of interest that will be plotted. Eg. temperature.
object	For autoplot: the output of the function ‘emp_spatial_cov’.
xlab	For autoplot: the label for x-axis.

Value

A spatialcov object with empirical covariance data organised spatially according to the number of strips and the lagged covariance.

Examples

# Dataframe example
library(dplyr)
data(NOAA_df_1990)
Tmax <- filter(NOAA_df_1990,
  proc == "Tmax" &
  month %in% 5:6 &
  year == 1993)
Tmax$t <- Tmax$julian - min(Tmax$julian) + 1
emp_df <- emp_spatial_cov(Tmax,
                lat_col = "lat",
                lon_col = "lon",
                t_col ="t",
                z_col = "z",
                lat_or_lon_strips = "lon",
                num_strips = 4,
                lag = 1)
autoplot(emp_df)

# Stars example
library(stars)
# Create a stars object from a data frame
precip_df <- NOAA_df_1990[NOAA_df_1990$proc == 'Precip', ] %>%
  filter(date >= "1992-02-01" & date <= "1992-02-05")
precip <- precip_df[ ,c('lat', 'lon', 'date', 'z')]
st_precip <- st_as_stars(precip, dims = c("lon", "lat", "date"))
emp_spatial_cov(st_precip)

stxplore documentation built on Feb. 16, 2023, 9:53 p.m.