BFpack (version 1.4.2)

BFpack-package: BFpack: Flexible Bayes factor testing of scientific expectations

Description

The R package BFpack provides tools for exploratory and confirmatory Bayesian hypothesis testing using Bayes factors and posterior probabilities under common statistical models. The main function `BF` needs a fitted model `x` as input argument. Depending on the class of the fitted model, a standard hypothesis test is executed by default. For example, if `x` is a fitted regression model of class `lm` then posterior probabilities are computed of whether each separate coefficient is zero, negative, or positive (assuming equal prior probabilities). If one has specific hypotheses with equality and/or order constraints on the parameters under the fitted model `x` then these can be formulated using the `hypothesis` argument (a character string), possibly together prior probabilities for the hypotheses via the `prior` argument (default all hypotheses are equally likely a priori), and the `complement` argument which is a logical stating whether the complement hypotheses should be included in the case (`TRUE` by default).

Use compilation for Fortran functions

Author

Maintainer: Joris Mulder

Authors:

• Caspar van Lissa [contributor]

• Donald R. Williams [contributor]

• Xin Gu [contributor]

• Anton Olsson-Collentine [contributor]

• Florian Boeing-Messing [contributor]

• Jean-Paul Fox [contributor]

Other contributors:

• Janosch Menke [contributor]

• Robbie van Aert [contributor]

• Barry Brown [contributor]

• James Lovato [contributor]

• Kathy Russell [contributor]

• Lapack 3.8 [contributor]

• Jack Dongarra [contributor]

• Jim Bunch [contributor]

• Cleve Moler [contributor]

• Gilbert Stewart [contributor]

• John Burkandt [contributor]

• Ashwith Rego [contributor]

• Alexander Godunov [contributor]

• Alan Miller [contributor]

• Jean-Pierre Moreau [contributor]

• The R Core Team [copyright holder]

References

Mulder, J., D.R. Williams, Gu, X., A. Tomarken, F. Böing-Messing, J.A.O.C. Olsson-Collentine, Marlyne Meyerink, J. Menke, J.-P. Fox, Y. Rosseel, E.J. Wagenmakers, H. Hoijtink., and van Lissa, C. (submitted). BFpack: Flexible Bayes Factor Testing of Scientific Theories in R. https://arxiv.org/abs/1911.07728

Mulder, J., van Lissa, C., Gu, X., Olsson-Collentine, A., Boeing-Messing, F., Williams, D. R., Fox, J.-P., Menke, J., et al. (2019). BFpack: Flexible Bayes Factor Testing of Scientific Expectations. (Version 0.2.1) https://CRAN.R-project.org/package=BFpack

See Also

Useful links:

• https://github.com/jomulder/BFpack

• Report bugs at https://github.com/jomulder/BFpack/issues

Examples

if (FALSE) {
# EXAMPLE 1. One-sample t test
ttest1 <- t_test(therapeutic, mu = 5)
print(ttest1)
# confirmatory Bayesian one sample t test
BF1 <- BF(ttest1, hypothesis = "mu = 5")
summary(BF1)
# exploratory Bayesian one sample t test
BF(ttest1)

# EXAMPLE 2. ANOVA
aov1 <- aov(price ~ anchor * motivation,data = tvprices)
BF1 <- BF(aov1, hypothesis = "anchorrounded = motivationlow;
                              anchorrounded < motivationlow")
summary(BF1)

# EXAMPLE 3. Logistic regression
fit <- glm(sent ~ ztrust + zfWHR + zAfro + glasses + attract + maturity +
   tattoos, family = binomial(), data = wilson)
BF1 <- BF(fit, hypothesis = "ztrust > zfWHR > 0;
                             ztrust > 0 & zfWHR = 0")
summary(BF1)

# EXAMPLE 4. Correlation analysis
set.seed(123)
cor1 <- cor_test(memory[1:20,1:3])
BF1 <- BF(cor1)
summary(BF1)
BF2 <- BF(cor1, hypothesis = "Wmn_with_Im > Wmn_with_Del > 0;
                              Wmn_with_Im = Wmn_with_Del = 0")
summary(BF2)
}