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keywords: design
title: Makes a polynomial model
description: Formulas are expanded to accommodate special functions for continuous and mixture variables.

keywords: design
title: Multple response creation
description: This function creates a multiple response matrix for its argument variables. When used on the lhs of the formula in lmp() or aovp() it will create a matrix containing one or more response columns from variables defined in the data argument.

keywords: design
title: Example application for Hidden Markov Models
description: The dishonest casino gives an example for the application of Hidden Markov Models. This example is taken from Durbin et. al. 1999: A dishonest casino uses two dice, one of them is fair the other is loaded. The probabilities of the fair die are (1/6,...,1/6) for throwing ("1",...,"6"). The probabilities of the loaded die are (1/10,...,1/10,1/2) for throwing ("1",..."5","6"). The observer doesn't know which die is actually taken (the state is hidden), but the sequence of throws (observations) can be used to infer which die (state) was used.

keywords: design
title: Display the scaled variance function for a design
description: This function computes the scaled variance function for a design, based on a specified model. Options include plotting separate curves for each of several directions from the center, or a contour plot for two of the design factors.

keywords: design
title: Join designs together into a blocked design
description: This implements the rsm package's building-block provisions for handling sequences of experiments. We often want to join two or more designs into one blocked design for purposes of analysis.

keywords: design
title: Find a good central-composite design
description: This function looks at all combinations of specified design parameters for central-composite designs, calculates other quantities such as the alpha values for rotatability and orthogonal blocking, imposes specified restrictions, and outputs the best combinations in a specified order. This serves as an aid in identifying good designs. The design itself can then be generated using ccd, or in pieces using cube, star, etc.

keywords: design
title: Generate a Box-Behnken design
description: This function can generate a Box-Behnken design in 3 to 7 factors, and optionally will block it orthogonally if there are 4 or 5 factors. It can also randomize the design.

keywords: design
title: Generate central-composite designs and associated building blocks
description: These functions generate central-composite designs, or building blocks thereof. They allow for flexible choices of replications, aliasing of predictors and fractional blocks, and choices of axis or ‘star’ points.

keywords: design
title: Expanding a formula
description: Formulas are expanded to accommodate special functions for continuous and mixture variables.