ao | R Documentation |
Functions used in quantile regression transformation models
ao(theta, lambda, symm = TRUE, omega = 0.001)
invao(x, lambda, symm = TRUE, replace = TRUE)
bc(x, lambda)
invbc(x, lambda, replace = TRUE)
mcjI(x, lambda, symm = TRUE, dbounded = FALSE, omega = 0.001)
invmcjI(x, lambda, symm = TRUE, dbounded = FALSE)
mcjII(x, lambda, delta, dbounded = FALSE, omega = 0.001)
invmcjII(x, lambda, delta, dbounded = FALSE)
x, theta |
numeric vector of singly ( |
lambda, delta |
transformation parameters. |
symm |
logical flag. If |
dbounded |
logical flag. If |
omega |
small constant to avoid numerical problems when |
replace |
logical flag. If |
These functions transform (back-transform) x
or theta
conditional on the parameters lambda
and theta
, using the Box–Cox (bc
), Aranda-Ordaz (ao
), Proposal I (mcjI
) and Proposal II (mcjII
) transformations.
Transformed or back-transformed values.
Marco Geraci
Aranda-Ordaz FJ. On two families of transformations to additivity for binary response data. Biometrika 1981;68(2):357-363.
Box GEP, Cox DR. An analysis of transformations. Journal of the Royal Statistical Society Series B-Statistical Methodology 1964;26(2):211-252.
Dehbi H-M, Cortina-Borja M, and Geraci M. Aranda-Ordaz quantile regression for student performance assessment. Journal of Applied Statistics. 2016;43(1):58-71.
Geraci M and Jones MC. Improved transformation-based quantile regression. Canadian Journal of Statistics 2015;43(1):118-132.
Jones MC. Connecting distributions with power tails on the real line, the half line and the interval. International Statistical Review 2007;75(1):58-69.
tsrq
, tsrq2
, rcrq
, nlrq2
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