Transcription of lowess — Lowess smoothing - Stata
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lowess — Lowess smoothing - Stata
Lowess smoothingDescriptionQuick startMenuSyntaxOptionsRemarks and examplesMethods and formulasAcknowledgmentReferencesAlso seeDescriptionlowesscarries out a locally weighted regression ofyvaronxvar, displays the graph, and optionallysaves the smoothed :lowessis computationally intensive and may therefore take a long time to run on aslow computer. Lowess calculations on 1,000 observations, for instance, require performing 1, startLocally weighted regression ofy1onxlowess y1 xAs above, but with a bandwidth of y1 x, bwidth(.4)With running-mean smoothinglowess y1 x, meanWithout the tricube weighting functionlowess y1 x, noweightGenerate a new variablevcontaining the smoothed values ofy1lowess y1 x, generate(v)Adjust the mean of the smoothed values to equal the mean of the unsmoothed valueslowess y1 x, adjustLowess smoothing of categorical variabley2onxin terms of the log of the odds ratiolowess y2 x, logitMenuStatistics>Nonparametric analysis> Lowess smoothing12 Lowess Lowess smoothingSyntaxlowessyvar xvar[if] [in] [,options]optionsDescriptionMainmeanrunn ing-mean smooth; default is running-line least squaresnoweightsuppress weighted regressions; default is tricube weighting functionbwidth(#)use#for the bandwidth; default isbwidth( )logittransform dependent variable to logitsadjustadjust smoothed mean to equal mean of dependent variabl
Locally weighted regression of y1 on x lowess y1 x As above, but with a bandwidth of 0.4 lowess y1 x, bwidth(.4) With running-mean smoothing lowess y1 x, mean Without the tricube weighting function lowess y1 x, noweight Generate a new variable v containing the smoothed values of y1 lowess y1 x, generate(v)
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