Scatter Plot between geo_distance vs maha_distance with geo- and maha- Quantile Threshold to Demonstrate the Outliers outside those threshold.

Usage

ec_plot_distance(
  x,
  geo_quantile = 0.99,
  maha_quantile = 0.99,
  iterative = TRUE,
  geo_distance = "geo_distance",
  maha_distance = "maha_distance"
)

Arguments

x: iteration_list derived from ec_flag_outlier can be used to plot these scatter plots between geo_distance vs maha_distance
geo_quantile: value with geo_quantile percentile would consider has threshold for geo_distance to derive the outlier. e.g. default 0.99
maha_quantile: value with maha_quantile percentile would consider has threshold for maha_distance to derive the outlier. e.g. default 0.99
iterative: = TRUE/FALSE, default set on TRUE, which provide a iterative loop to check maps of each iteration of listed outcome of outlier probability, if it is FALSE, loop exit with first iteration outcome of outlier probability.
geo_distance: default set on "geo_distance", this column has calculated distance - output of ec_flag_outlier
maha_distance: default set on "maha_distance", this column has calculated distance - output of ec_flag_outlier

Value

A list of plots for each iteration outcome

Examples

df1 <- data.frame(
  latitude = runif(5, 30, 35),
  longitude = runif(5, -120, -115),
  temperature = rnorm(5, 15, 2),
  pH = rnorm(5, 8, 0.1),
  geo_distance = runif(5, 0, 100),
  maha_distance = runif(5, 0, 10)
)
df2 <- data.frame(
 latitude = runif(5, 30, 35),
 longitude = runif(5, -120, -115),
 temperature = rnorm(5, 16, 2),
 pH = rnorm(5, 7.9, 0.1),
 geo_distance = runif(5, 0, 100),
 maha_distance = runif(5, 0, 10)
)

iteration_list <- list(df1, df2)#Store both data frames in a list

iteration_list <- list(df1, df2)
plot <- ec_plot_distance(iteration_list, geo_quantile = 0.99, maha_quantile = 0.99,
iterative = TRUE)

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