Package SPIn. R topics documented: February 19, Type Package
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1 Type Package Package SPIn February 19, 2015 Title Simulation-efficient Shortest Probability Intervals Version 1.1 Date Author Ying Liu Maintainer Ying Liu Depends R (>= 1.8.0), quadprog An optimal weighting strategy to compute simulation-efficient shortest probability intervals (spins). License GPL (>= 2) NeedsCompilation no Repository CRAN Date/Publication :57:16 R topics documented: SPIn-package bootspin plot.spin SPIn Inde 6 SPIn-package Simulation Efficient Shortest Probability Intervals Details Implement an optimal weighting strategy to compute simulation efficient shortest probability intervals (spin s). 1
2 2 bootspin Package: SPIn Type: Package Version: 1.1 Date: License: GPL (>= 2) This package contains functions for constructing and plotting simulation efficient shortest probability intervals. Ying Liu Maintainer: Ying Liu bootspin SPIn with Bootstrap Compute the shortest probability interval (spin) using SPIn with bootstrap. Usage bootspin(, n.boot = 50, = 0.95, bw = 0, lb = -Inf, ub = Inf, l = NA, u = NA) Arguments n.boot bw lb,ub l,u Number of bootstraps. Scalar, the idence level desired. Scalar, the bandwidth of the weighting kernel in terms of sample points. If not specified, sqrt(n) will be used, where n is the sample size. Scalars, the lower and upper bounds of the distribution. If specified, a pseudosample point equal to the corresponding bound will be added. Scalars, weighting centers (if provided). Details spin.boot computes the shortest probability interval for a distribution using SPIn with bootstrap.
3 plot.spin 3 Value spin.boot returns an object of class SPIn. An object of class SPIn is a list containing the following components: spin A vector of length 2 with the lower and upper endpoints of the interval. The idence level. w.l,w.u Vectors of the computed weights. l.l,l.u,u.l,u.u Endpoints of the weights. Note This function assumes that the distribution is unimodal, and computes only 1 interval, not the set of intervals that are appropriate for multimodal distributions. Ying Liu yliu@stat.columbia.edu See Also plot.spin,spin Eamples <- rgamma(100,3) bootspin() plot.spin Plot the Results from SPIn or bootspin Plot the histogram, the kernel density estimate, the shortest probability interval and the central interval. Usage ## S3 method for class SPIn plot(,...)
4 4 SPIn Arguments... See plot. Ying Liu See Also SPIn object, result of SPIn or bootspin. SPIn,bootSPIn Eamples <- rgamma(100,3) r <- bootspin() plot(r) SPIn Simulation Efficient Shortest Probability Intervals Compute the shortest probability interval (spin) using an optimal weighting strategy. Usage SPIn(, = 0.95, bw = 0, lb = -Inf, ub = Inf, l=na, u=na) Arguments bw lb,ub l,u Scalar, the idence level desired. Scalar, the bandwidth of the weighting kernel in terms of sample points. If not specified, sqrt(n) will be used, where n is the sample size. Scalars, the lower and upper bounds of the distribution. If specified, a pseudosample point equal to the corresponding bound will be added. Scalars, weighting centers (if provided). Details SPIn computes the shortest probability interval for a distribution using an optimal weighting strategy. Quadratic programming is used to determine the optimal weights.
5 SPIn 5 Value Note SPIn returns an object of class SPIn. An object of class SPIn is a list containing the following components: spin A vector of length 2 with the lower and upper endpoints of the interval. The idence level. w.l,w.u Vectors of the computed weights. l.l,l.u,u.l,u.u Endpoints of the weights. This function assumes that the distribution is unimodal, and computes only 1 interval, not the set of intervals that are appropriate for multimodal distributions. Ying Liu yliu@stat.columbia.edu See Also bootspin,plot.spin Eamples <- rgamma(100,3) SPIn()
6 Inde Topic \tetasciitildekwd1 bootspin, 2 plot.spin, 3 SPIn, 4 Topic \tetasciitildekwd2 bootspin, 2 plot.spin, 3 SPIn, 4 bootspin, 2, 4, 5 class, 3, 5 plot.spin, 3, 3, 5 SPIn, 3, 4, 4 SPIn-package, 1 6
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