| Bolstad-package | Bolstad Functions |
| as.data.frame.Bolstad | as.data.frame.Bolstad |
| bayes.lin.reg | Bayesian inference for simple linear regression |
| bayes.lm | Bayesian inference for multiple linear regression |
| bayes.t.test | Bayesian t-test |
| bayes.t.test.default | Bayesian t-test |
| bayes.t.test.formula | Bayesian t-test |
| bears | bears |
| binobp | Binomial sampling with a beta prior |
| binodp | Binomial sampling with a discrete prior |
| binogcp | Binomial sampling with a general continuous prior |
| binomixp | Binomial sampling with a beta mixture prior |
| Bolstad | Bolstad Functions |
| Bolstad.control | Control Bolstad functions |
| cdf | Cumulative distribution function generic |
| cdf.Bolstad | Cumulative distribution function generic |
| createPrior | Create prior generic |
| createPrior.default | Create prior default method |
| decomp | Plot the prior, likelihood, and posterior on the same plot. |
| IQR | Interquartile Range generic |
| lines.Bolstad | Lines method for Bolstad objects |
| mean.Bolstad | Calculate the posterior mean |
| median.Bolstad | Median generic |
| moisture.df | Moisture data |
| mvnmvnp | Bayesian inference on a mutlivariate normal (MVN) mean with a multivariate normal (MVN) prior |
| normdp | Bayesian inference on a normal mean with a discrete prior |
| normgcp | Bayesian inference on a normal mean with a general continuous prior |
| normmixp | Bayesian inference on a normal mean with a mixture of normal priors |
| normnp | Bayesian inference on a normal mean with a normal prior |
| nvaricp | Bayesian inference for a normal standard deviation with a scaled inverse chi-squared distribution |
| plot.Bolstad | Plot method for objects of type Bolstad |
| poisdp | Poisson sampling with a discrete prior |
| poisgamp | Poisson sampling with a gamma prior |
| poisgcp | Poisson sampling with a general continuous prior |
| print.Bolstad | Print method for objects of class 'Bolstad' |
| print.sintegral | Generic print method |
| print.sscsamp | Print method for objects of class 'sscsample' |
| quantile.Bolstad | Posterior quantiles |
| sd | Standard deviation generic |
| sd.Bolstad | Posterior standard deviation |
| sintegral | Numerical integration using Simpson's Rule |
| slug | Slug data |
| sscsample | Simple, Stratified and Cluster Sampling |
| sscsample.data | Data for simple random sampling, stratified sampling, and clusting sampling experiments |
| summary.Bolstad | Summarizing Bayesian Multiple Linear Regression |
| var | Variance generic |
| xdesign | Monte Carlo study of randomized and blocked designs |