The np Package - NexTag Supports Open Source Initiatives

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2 cps71npudensbw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41npksum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50npplot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58npplreg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70npplregbw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76npqcmstest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83npqreg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86npreg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90npregbw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100npsigtest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107npindex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110npindexbw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119npscoef . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125npscoefbw . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130se . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136uocquantile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137Index 138cps71Canadian High School Graduate EarningsDescriptionCanadian cross-section wage data consisting of a random sample taken from the 1971 CanadianCensus Public Use Tapes for male individuals having common education (grade 13). There are 205observations in total.Usagedata("cps71")FormatA data frame with 2 columns, and 205 rows.logwage the first column, of type numericage the second column, of type integerSourceAman UllahReferencesPagan, A. and A. Ullah (1999), Nonparametric Econometrics, Cambridge University Press.
Italy 3Examplesdata("cps71")attach(cps71)plot(age, logwage, xlab="Age", ylab="log(wage)")detach(cps71)ItalyItalian GDP PanelDescriptionItalian GDP growth panel for 21 regions covering the period 1951-1998 (millions of Lire, 1990=base).There are 1008 observations in total.Usagedata("Italy")FormatA data frame with 2 columns, and 1008 rows.year the first column, of type integergdp the second column, of type numeric: millions of Lire, 1990=baseSourceGiovanni BaiocchiReferencesBaiocchi, G. (2006), “Economic Applications of Nonparametric Methods,” Ph.D. Thesis, Universityof York.Examplesdata("Italy")attach(Italy)plot(ordered(year), gdp, xlab="Year (ordered factor)",ylab="GDP (millions of Lire, 1990=base)")detach(Italy)
Page 1: The np PackageFebruary 16, 2008Vers
Page 5 and 6: wage1 5Examplesdata("oecdpanel")att
Page 7 and 8: gradients 7## S3 method for class '
Page 9 and 10: np 9A variety of bandwidth methods
Page 11 and 12: npcmstest 11npcmstestKernel Consist
Page 13 and 14: npcmstest 13ReferencesAitchison, J.
Page 15 and 16: npcdens 15npcdensKernel Conditional
Page 17 and 18: npcdens 17Valuenpcdens returns a co
Page 19 and 20: npcdens 19# Gaussian kernel (defaul
Page 21 and 22: npcdens 21# (1993) (see their descr
Page 23 and 24: npcdensbw 23fit
Page 25 and 26: npcdensbw 25na.actionxdatydatbwspro
Page 27 and 28: npcdensbw 27data. The approach is b
Page 29 and 30: npconmode 29# depending on the spee
Page 31 and 32: npconmode 31tydatexdateydata one (1
Page 33 and 34: npconmode 33lwt,family=binomial(lin
Page 35 and 36: npudens 35npudensKernel Density and
Page 37 and 38: npudens 37Author(s)Tristen Hayfield
Page 39 and 40: npudens 39# EXAMPLE 1 (INTERFACE=DA
Page 41 and 42: npudensbw 41library("datasets")data
Page 43 and 44: npudensbw 43bwsa bandwidth specific
Page 45 and 46: npudensbw 45fvalobjective function
Page 47 and 48: npudensbw 47# previous examples.bw
Page 49 and 50: npudensbw 49# previous examples.bw
Page 51 and 52: npksum 51Argumentsformuladatanewdat
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npksum 53Usage IssuesIf you are usi
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npksum 55# the bandwidth object its
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npksum 57ss
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npplot 59plot.behavior = c("plot","
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npplot 61xtrim = 0.0,neval = 50,com
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npplot 63xdatydatzdatxqyqzqxtrimytr
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npplot 65DetailsValuenpplot is a ge
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npplot 67year.seq
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npplot 69# npplot(). When npplot()
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npplreg 71## S3 method for class 'c
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npplreg 73residR2MSEMAEMAPECORRSIGN
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npplreg 75# Plot the regression sur
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npplregbw 77and dependent data), an
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npplregbw 79Detailsnpplregbw implem
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npplregbw 81x2
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npqcmstest 83npqcmstestKernel Consi
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npqcmstest 85Author(s)Tristen Hayfi
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npqreg 87ftol = 1.19209e-07,tol = 1
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npqreg 89Li, Q. and J.S. Racine (20
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npreg 91Usagenpreg(bws, ...)## S3 m
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npreg 93residR2MSEMAEMAPECORRSIGNif
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npreg 95summary(model)# Use npplot(
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npreg 97# - this may take a few min
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npreg 99# then a noisy samplen
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npregbw 101## S3 method for class '
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npregbw 103ckerorderukertypeokertyp
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npregbw 105ReferencesAitchison, J.
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npsigtest 107bw
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npsigtest 109Author(s)Tristen Hayfi
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npindex 111Usagenpindex(bws, ...)##
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npindex 113MAEMAPECORRSIGNif method
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npindex 115x2
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npindex 117# x1 is chi-squared havi
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npindexbw 119# plotting via persp()
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npindexbw 121methodnmultithe single
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npindexbw 123allows one to deploy t
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npscoef 125x1
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npscoef 127Valueeydatezdaterrorsres
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npscoef 129# We could manually plot
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npscoefbw 131optim.abstol,optim.max
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npscoefbw 133optim.maxattemptsmaxim
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npscoefbw 135ReferencesAitchison, J
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uocquantile 137uocquantileCompute Q
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INDEX 139npconmode, 29npindex, 110n
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