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Showing results 1 to 10 of 678.


Function poly.formula [lmPerm v2.1.0]
keywords
design
title
Makes a polynomial model
description
Formulas are expanded to accommodate special functions for continuous and mixture variables.
Function multResp [lmPerm v2.1.0]
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.
Function dishonestCasino [HMM v1.0]
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.
Function BDP2workflow [BDP2 v0.1.3]
keywords
design
title
Shiny app for workflow
description
Starts a shiny app in the web browser. It provides a workflow to choose design parameters single-arm trial with a binary endpoint (response, success) and interim efficacy and futility analyses as well as routines to determine and visualize operating characteristics. Also Word/pdf/html reports can be generated.
Function BDP2 [BDP2 v0.1.3]
keywords
design
title
Operating characteristics of a single-arm trial with a binary endpoint
description
Determines the operating characteristics of a single-arm trial with a binary endpoint (response, success) and interim efficacy and futility analyses. Declaration of efficacy and futility (including possibly early stopping) is based on the posterior probability that the true response rate is at least pE , pF respectively.
Function varfcn [rsm v2.10]
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.
Function djoin [rsm v2.10]
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.
Function ccd.pick [rsm v2.10]
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.
Function bbd [rsm v2.10]
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.
Function ccd [rsm v2.10]
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.