{smcl} {* *! version 1.1.1 20jan2013}{...} {vieweralsosee "dftol" "help dftol"}{...} {viewerjumpto "Syntax" "dftolss##syntax"}{...} {viewerjumpto "Description" "dftolss##description"}{...} {viewerjumpto "Remarks" "dftolss##remarks"}{...} {viewerjumpto "Options" "dftolss##options"}{...} {viewerjumpto "Examples" "dftolss##examples"}{...} {viewerjumpto "Saved results" "dftolss##savedresults"}{...} {viewerjumpto "Author" "dftolss##author"}{...} {viewerjumpto "References" "dftolss##references"}{...} {title:Title} {p2colset 6 17 21 2}{...} {p2col:{hi:dftolss} {hline 2}}Sample size calculation for distribution-free tolerance intervals{p_end} {p2colreset}{...} {marker syntax}{...} {title:Syntax} {phang2} {cmd:dftolss} {cmd:,} [{opt c:onf(#)} {opt b:eta(#)} {opt r(#)}] {synoptset 12 tabbed}{...} {synopthdr} {synoptline} {synopt:{opt c:onf(#)}}set confidence level of the tolerance interval; default is {cmd:conf(95)}{p_end} {synopt:{opt b:eta(#)}}set percentage of the population covered by the tolerance interval; default is {cmd:beta(95)}{p_end} {synopt:{opt r(#)}}set the number of blocks removed; default is {cmd:r(2)}{p_end} {synoptline} {marker description}{...} {title:Description} {pstd} {cmd:dftolss} computes the smallest sample size for the tolerance intervals obtained removing {cmd:r(#)} blocks to contain, at confidence level {cmd:conf(#)%}, at least a percentage {cmd:beta(#)%} of the sampled population. See also {help dftol}.{p_end} {marker remarks}{...} {title:Remarks} {pstd} {cmd:dftolss} requires that the Stata module -moremata- (Jann, 2005) be installed.{p_end} {marker options}{...} {title:Options} {phang} {opt conf(#)} specifies the confidence level of the tolerance interval as a percentage. The default is {cmd:conf(95)}, meaning a 95% confidence level. {phang} {opt beta(#)} specifies the percentage of the sampled population to be contained in the tolerance interval. The default is {cmd:beta(95)}, meaning a percentage equal to 95%. {phang} {opt r(#)} specifies the number of blocks removed. The default is {cmd:r(2)}, which, according to the definition of block (see Murphy, 1948) means that the endpoints of the tolerance interval would be the smallest and largest observations of the sample. Note that for {cmd:r(1)}, i.e. when only one block is removed, the interval reduces to a one-sided lower (alternatively, upper) tolerance bound. {marker examples}{...} {title:Examples} {cmd: . dftolss} {cmd: . dftolss, c(90) b(90)} {cmd: . dftolss, c(99) b(99) r(4)} {marker savedresults}{...} {title:Saved results} {cmd:dftolss} saves the following in {cmd:r()}: Scalars {p2colset 5 20 22 2}{...} {p2col:{cmd:r(n)}}sample size){p_end} {p2colreset}{...} {marker author}{...} {title:Author} {pstd}Ignacio López de Ullibarri{p_end} {pstd}Department of Mathematics{p_end} {pstd}University of A Coruña, Spain{p_end} {pstd}E-mail: {browse "mailto:ilu@udc.es":ilu@udc.es}{p_end} {marker references}{...} {title:References} {phang} Jann B (2005), {it:moremata: Stata module (Mata) to provide various functions}, available from {browse "http://ideas.repec.org/c/boc/bocode/s455001.html"} {phang} Murphy RB (1948), Non-parametric tolerance limits, {it:Annals of Mathematical Statistics}, 19: 581-589