The np Package - NexTag Supports Open Source Initiatives

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56 npksum# If you wished to compute the kernel sum for a set of evaluation points,# you first generate the set of points then feed this to npksum,# e.g., for the set (20, 30, ..., 60) we would useage.seq
npksum 57ss
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The np PackageFebruary 16, 2008Vers
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Italy 3Examplesdata("cps71")attach(
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
Page 53 and 54: npksum 53Usage IssuesIf you are usi
Page 55: npksum 55# the bandwidth object its
Page 59 and 60: npplot 59plot.behavior = c("plot","
Page 61 and 62: npplot 61xtrim = 0.0,neval = 50,com
Page 63 and 64: npplot 63xdatydatzdatxqyqzqxtrimytr
Page 65 and 66: npplot 65DetailsValuenpplot is a ge
Page 67 and 68: npplot 67year.seq
Page 69 and 70: npplot 69# npplot(). When npplot()
Page 71 and 72: npplreg 71## S3 method for class 'c
Page 73 and 74: npplreg 73residR2MSEMAEMAPECORRSIGN
Page 75 and 76: npplreg 75# Plot the regression sur
Page 77 and 78: npplregbw 77and dependent data), an
Page 79 and 80: npplregbw 79Detailsnpplregbw implem
Page 81 and 82: npplregbw 81x2
Page 83 and 84: npqcmstest 83npqcmstestKernel Consi
Page 85 and 86: npqcmstest 85Author(s)Tristen Hayfi
Page 87 and 88: npqreg 87ftol = 1.19209e-07,tol = 1
Page 89 and 90: npqreg 89Li, Q. and J.S. Racine (20
Page 91 and 92: npreg 91Usagenpreg(bws, ...)## S3 m
Page 93 and 94: npreg 93residR2MSEMAEMAPECORRSIGNif
Page 95 and 96: npreg 95summary(model)# Use npplot(
Page 97 and 98: npreg 97# - this may take a few min
Page 99 and 100: npreg 99# then a noisy samplen
Page 101 and 102: npregbw 101## S3 method for class '
Page 103 and 104: npregbw 103ckerorderukertypeokertyp
Page 105 and 106: npregbw 105ReferencesAitchison, J.
Page 107 and 108:
npsigtest 107bw
Page 109 and 110:
npsigtest 109Author(s)Tristen Hayfi
Page 111 and 112:
npindex 111Usagenpindex(bws, ...)##
Page 113 and 114:
npindex 113MAEMAPECORRSIGNif method
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npindex 115x2
Page 117 and 118:
npindex 117# x1 is chi-squared havi
Page 119 and 120:
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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