| Type: | Package |
| Title: | Multicore Multivariable Isotonic Regression |
| Version: | 0.1.2 |
| Description: | The goal of 'McMiso' is to provide functions for isotonic regression when there are multiple independent variables. The functions solve the optimization problem using recursion and leverage parallel computing to improve speed, and are useful for situations with relatively large number of covariates. The estimation method follows the projective Bayes solution described in Cheung and Diaz (2023) <doi:10.1093/jrsssb/qkad014>. |
| Depends: | R (≥ 4.0.0) |
| Imports: | dplyr, future (≥ 1.33.0), stats |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| NeedsCompilation: | no |
| Packaged: | 2025-11-18 15:48:18 UTC; yingkuencheung |
| Author: | Cheung Ken [aut, cre] |
| Maintainer: | Cheung Ken <yc632@cumc.columbia.edu> |
| Repository: | CRAN |
| Date/Publication: | 2025-11-21 15:40:08 UTC |
Probabilistic Bayesian classifier
Description
Probabilistic Bayesian classifier
Usage
PBclassifier(X, y, method = "DU", a0 = 0.25, b0 = 0.25, t0 = 0.5)
Arguments
X |
numeric matrix of doses |
y |
numeric response vector |
method |
character, either "DU" or "UD" |
a0 |
numeric, prior alpha |
b0 |
numeric, prior beta |
t0 |
numeric, threshold |
Value
A list with class "pbc"
References
Cheung YK, Diaz KM. Monotone response surface of multi-factor condition: estimation and Bayes classifiers. *J R Stat Soc Series B Stat Methodol.* 2023 Apr;85(2):497-522. doi: 10.1093/jrsssb/qkad014. Epub 2023 Mar 22. PMID: 38464683; PMCID: PMC10919322.
Examples
A <- as.matrix(expand.grid(rep(list(0:1), 6)))
set.seed(2025)
X <- A[sample(nrow(A),size=500, replace = TRUE),]
y <- as.numeric(rowSums(X)>=3)
PBclassifier(X,y)
Fit Bayesian misclassification model (binary)
Description
Fit Bayesian misclassification model (binary)
Usage
miso(X, y, incr = 0.01)
Arguments
X |
numeric matrix |
y |
numeric response vector |
incr |
numeric, increment for threshold grid |
Value
A list containing fitted parameters
References
Cheung YK, Diaz KM. Monotone response surface of multi-factor condition: estimation and Bayes classifiers. *J R Stat Soc Series B Stat Methodol.* 2023 Apr;85(2):497-522. doi: 10.1093/jrsssb/qkad014. Epub 2023 Mar 22. PMID: 38464683; PMCID: PMC10919322.
Examples
A <- as.matrix(expand.grid(rep(list(0:1), 6)))
set.seed(2025)
X <- A[sample(nrow(A),size=500, replace = TRUE),]
y <- as.numeric(rowSums(X)>=3)
miso(X,y)
S3 predict method for class "pbc"
Description
S3 predict method for class "pbc"
Usage
## S3 method for class 'pbc'
predict(object, Xnew, ...)
Arguments
object |
object of class "pbc" |
Xnew |
numeric matrix of inputs |
... |
additional arguments (not used) |
Value
List containing predictions
Examples
A <- as.matrix(expand.grid(rep(list(0:1), 6)))
set.seed(2025)
X <- A[sample(nrow(A),size=500, replace = TRUE),]
y <- as.numeric(rowSums(X)>=3)
fit <- PBclassifier(X,y)
predict(fit,X)