loss_functions: Loss functions

In mladenjovanovic/bmbstats: Bootstrap Magnitude-Based Statistics

Description

Loss functions

Quadratic loss

Absolute loss

Difference loss

Huber loss

Hinge loss

Usage

loss_quadratic(
  observed,
  predicted,
  SESOI_lower = 0,
  SESOI_upper = 0,
  negative_weight = 1,
  positive_weight = 1,
  na.rm = FALSE
)

loss_absolute(
  observed,
  predicted,
  SESOI_lower = 0,
  SESOI_upper = 0,
  negative_weight = 1,
  positive_weight = 1,
  na.rm = FALSE
)

loss_difference(
  observed,
  predicted,
  SESOI_lower = 0,
  SESOI_upper = 0,
  negative_weight = 1,
  positive_weight = 1,
  na.rm = FALSE
)

loss_huber(
  observed,
  predicted,
  SESOI_lower = 0,
  SESOI_upper = 0,
  negative_weight = 1,
  positive_weight = 1,
  na.rm = FALSE
)

loss_hinge(
  observed,
  predicted,
  SESOI_lower = 0,
  SESOI_upper = 0,
  negative_weight = 1,
  positive_weight = 1,
  exponent = 1,
  na.rm = FALSE
)

Arguments

observed	Numeric vector
predicted	Numeric vector
SESOI_lower	Lower smallest effect size of interest threshold
SESOI_upper	Upper smallest effect size of interest threshold
negative_weight	How should negative residuals be weighted? Default is 1
positive_weight	How should positive residuals be weighted? Default is 1
na.rm	Should NAs be removed? Default is FALSE
exponent	Numeric scalar. Default is 1.

Examples

data("yoyo_mas_data")

model <- lm(MAS ~ YoYoIR1, yoyo_mas_data)

observed <- yoyo_mas_data$MAS
predicted <- predict(model)

SESOI_lower <- -0.5
SESOI_upper <- 0.5

# Square loss
loss_quadratic(
  observed = observed,
  predicted = predicted,
  SESOI_lower = SESOI_lower,
  SESOI_upper = SESOI_upper
)

# Absolute loss
loss_absolute(
  observed = observed,
  predicted = predicted,
  SESOI_lower = SESOI_lower,
  SESOI_upper = SESOI_upper
)

# Difference
loss_difference(
  observed = observed,
  predicted = predicted,
  SESOI_lower = SESOI_lower,
  SESOI_upper = SESOI_upper
)

# Huber loss
loss_huber(
  observed = observed,
  predicted = predicted,
  SESOI_lower = SESOI_lower,
  SESOI_upper = SESOI_upper
)

# Hinge loss
loss_hinge(
  observed = observed,
  predicted = predicted,
  SESOI_lower = SESOI_lower,
  SESOI_upper = SESOI_upper
)

mladenjovanovic/bmbstats documentation built on Aug. 5, 2020, 4:20 p.m.