XploRe Quantlets: XploRe Application Guide

* XploRe - the interactive statistical computing environment


  • To use these quantlets with your local XploRe version, save the files (****.xpl) on your local disk and execute them from XploRe.
  • Within a quantlet page you can also use the Execute or Edit button to directly send the quantlets to an XQS.


aslm01   (aslm01.xpl)
calculates the periodogram and spectral density for the returns and differences of returns in dbs50.dat

aslm02   (aslm02.xpl)
calculates the histogram, qq plot and kernel density estimator returns of DBS50

aslm03   (aslm03.xpl)
performs the long-memory analysis of returns of DBS50

cart01   (cart01.xpl)
displays 100 simulated data from the function f(x1,x2)

cart02   (cart02.xpl)
finds the initial regression tree for 100 simulated data from function f(x1,x2)

cart03   (cart03.xpl)
finds the final regression tree for 100 simulated data from function f(x1,x2)

cart04   (cart04.xpl)
finds the initial regression tree for 20% of Boston Housing Data

cart05   (cart05.xpl)
finds the subtree consisting of 20 leaves for 20% of Boston Housing Data

cart06   (cart06.xpl)
finds the cross-validated regression tree for 20% of Boston Housing Data

cart07   (cart07.xpl)
finds the final regression tree for 20% of Boston Housing Data

cart08   (cart08.xpl)
finds the final regression tree for 20% of Boston Housing Data with numbers of observations and mean values

cart09   (cart09.xpl)
transforms the density data to regression data for bank swiss note data, applies the CART method to them and shows the projected cuts (for six nodes)

cart10   (cart10.xpl)
transforms the density data to regression data for bank swiss note data, applies the CART method to them and shows the projected cuts (for fourteen nodes)

clust01   (clust01.xpl)
computes the distance with the "maximum" metric

clust02   (clust02.xpl)
computes the distance with "lpdist" metric (here: p=2)

clust03   (clust03.xpl)
computes the distance for binary data with the "tanimoto" metric

clust04   (clust04.xpl)
computes the dendrogram with the single linkage method

clust05   (clust05.xpl)
computes the dendrogram with the complete linkage method

clust06   (clust06.xpl)
computes the dendrogram with the average linkage method

clust07   (clust07.xpl)
computes the dendrogram with the centroid linkage method

clust08   (clust08.xpl)
computes the dendrogram with the median link method

clust09   (clust09.xpl)
shows the dendrogram with Ward method

clust10   (clust10.xpl)
shows the dendrogram with Ward method for data columns and rows

clust11   (clust11.xpl)
applies the divisive methods and compares the results between estimated and true partitions

clust12   (clust12.xpl)
clusters with the k-means method

clust13   (clust13.xpl)
clusters with the adaptive k-means method

clust14   (clust14.xpl)
clusters with the hard-c-means method for the butterfly data

clust15   (clust15.xpl)
clusters with fuzzy-c-means method for the butterfly data

clust16   (clust16.xpl)
compares the Ward and Fuzzy-C-Means method for the Swiss Banknote data with two clusters

clust17   (clust17.xpl)
compares the Ward and Fuzzy-C-Means method for the Swiss Banknote data with three clusters

corre01   (corre01.xpl)
(correspondence) analysis of eye-hair data set

corre02   (corre02.xpl)
(correspondence) analysis of the media dataset

dpls01   (dpls01.xpl)
example for creating and estimating a simple model with DPLS for simulated data

eiv01   (eiv01.xpl)
estimates the parameters of eiv model for simulated data swith known reliability ratio

eiv02   (eiv02.xpl)
estimates the parameters of eiv model for pheasant data with known ratio of the measurement errors

eiv03   (eiv03.xpl)
estimates the parameters of eiv model for corn data with known variance of the measurement error

eiv04   (eiv04.xpl)
estimates the parameters of eiv model for corn data with known variace of the measurement error - modified method

eiv05   (eiv05.xpl)
estimates the parameters of eiv model for Alaskan earthquakes data with linear instrumental variable

eiv06   (eiv06.xpl)
estimates the vector of parameters of eiv model for simulated data using eivvec1

eiv07   (eiv07.xpl)
estimates the vector of parameters of eiv model for simulated data using eivvec2

eiv08   (eiv08.xpl)
estimates the vector of parameters of eiv model for simulated data - method of instrumental variables

eiv09   (eiv09.xpl)
estimates the parameters of nonlinear eiv model for Heidelberg cement factory data - regression calibration

eiv10   (eiv10.xpl)
estimates the parameters of nonlinear eiv model for Heidelberg cement factory data - simulation extrapolation

eiv11   (eiv11.xpl)
estimates the parameters of partially linear eiv model for simulated data

flts01   (flts01.xpl)
plot original and logged time series of lynx data s

flts02   (flts02.xpl)
Nadaraya-Watson estimate of NAR(1) model for lynx data

flts03   (flts03.xpl)
Local linear estimate of NAR(1) model for lynx data

flts04   (flts04.xpl)
Bandwidth selection for Nadaraya-Watson estimates of NAR(1) model for lynx data

flts05   (flts05.xpl)
Diagnostics for local linear estimates of NAR(1) model for lynx data

flts06   (flts06.xpl)
Confidence intervals for NAR(1) model for lynx data

flts07   (flts07.xpl)
Local quadratic estimation of first and second derivatives for NAR(1) model

flts08   (flts08.xpl)
Local constant and linear estimate of NAR(2) model for lynx data

flts09   (flts09.xpl)
selects lags of nonlinear autoregressive process for lynx data using CAFPE criterion

flts10   (flts10.xpl)
plots the nonparametric estimate of a nonlinear regression function for the lynx data set

flts11   (flts11.xpl)
plots original and logged time series of exchange rates

flts12   (flts12.xpl)
selects lags for conditional mean of nonlinear AR process for exchange rate returns using CAFPE criterion

flts13   (flts13.xpl)
plots conditional mean function for lags 1, 3, autocorrelation function of residuals and uses these residuals to select lags of nonlinear conditional volatility function for exchange rate returns using CAFPE criterion

flts14   (flts14.xpl)
plots the nonparametric estimate of a two-dimensional function of the conditional standard deviation for exchange rate returns and autocorrelation function of residuals

gam01   (gam01.xpl)
simulates data with additive structure

gam02   (gam02.xpl)
estimates additive model for simulated data

gam03   (gam03.xpl)
estimates additive partially linear model for simulated data

gam04   (gam04.xpl)
estimates additive or additive partially linear model for simulated data using backfitting

gam05   (gam05.xpl)
estimates GAM for simulated data

gam06   (gam06.xpl)
estimates generalized additive partially linear model for for simulated data

gam07   (gam07.xpl)
estimates bivariate marginal influence for simulated data

gam08   (gam08.xpl)
estimates additive model with interaction term for simulated data

gam09   (gam09.xpl)
estimates additive model using marginal integration

gam10   (gam10.xpl)
calls the interactive quantlet gamfit for simulated data

gam11   (gam11.xpl)
analysis of components for simulated data

gam12   (gam12.xpl)
test for the interaction term using intertest1

gam13   (gam13.xpl)
test for the interaction term using intertest2

gam14   (gam14.xpl)
estimates the additive components, significant directions and the regression on principal components for simulated data

gam15   (gam15.xpl)
analysis of the Wisconsin farm data

gplm01   (gplm01.xpl)
Summary statistics for the Credit data.

gplm02   (gplm02.xpl)
GPLM estimation for the Credit data (using the default Speckman algorithm).

gplm03   (gplm03.xpl)
GPLM estimation for the Credit data using profile likelihood.

gplm04   (gplm04.xpl)
GPLM estimation for the Credit data with gplmcore.

gplm05   (gplm05.xpl)
Testing the GLM (with linear index) against the GPLM. The GPLM estimation for the Credit data uses profile likelihood.

gplm06   (gplm06.xpl)
Testing the GLM (with linear index + interaction) against the GPLM. The GPLM estimation for the Credit data uses profile likelihood.

growdist   (growdist.xpl)
analysis of worldwide income distribution

haz00   (haz00.xpl)
generates the pseudo-random data set haz01.dat

haz01   (haz01.xpl)
explains the use of quantlet hazdat which organizes the data for hazard regression in XploRe

haz02   (haz02.xpl)
explains the use of quantlet atrisk which calculates the risk set for a given time

haz03   (haz03.xpl)
explains the use of quantlet haznar which calculates the size of the risk set

haz04   (haz04.xpl)
calculates and plots the Kaplan-Meier estimator for simulated data

haz05   (haz05.xpl)
explains the use of quantlet hazregll which calculates the log-likelihood and its derivatives

haz06   (haz06.xpl)
estimates the parameters of Cox model for simulated data

haz07   (haz07.xpl)
estimates and plots the cumulative baseline hazard and baseline survival functions for simulated data

haz08   (haz08.xpl)
estimates and plots the conditional survival function for simulated data

haz09   (haz09.xpl)
tests the significance of the parameters estimates in Cox model for simulated data

haz10   (haz10.xpl)
hazard regression analysis for length of stay in nursing homes

longmem01   (longmem01.xpl)
calculates Newey and West estimates of the variance for DM/US exchange rates dataset

longmem02   (longmem02.xpl)
Calculates Lo's statistics for the DM/US data set

longmem03   (longmem03.xpl)
calculates KPSS statistics for the DM/US data set

longmem04   (longmem04.xpl)
calculates rescaled variance test V/S for DM/US dataset

longmem05   (longmem05.xpl)
calculates Lobato-Robinson test for DM/US data set using default bandwidth

longmem06   (longmem06.xpl)
calculates Lobato-Robinson test for DM/US data set for a vector of bandwidths

longmem07   (longmem07.xpl)
calculates Geweke and Porter-Hudak estimator of the long-memory parameter for DM/US dataset

longmem08   (longmem08.xpl)
calculates Robinson averaged periodogram estimator for DM/US data set

longmem09   (longmem09.xpl)
calculates the semiparametric estimator of the long-memory parameter for DM/US data set

ls01   (ls01.xpl)
estimation of phonecal data set by OLS

ls02   (ls02.xpl)
estimation of an artificial data set by OLS with graphical output and residual plot

ls03   (ls03.xpl)
estimation of stacklos data set by OLS

ls04   (ls04.xpl)
estimation of stacklos data set by OLS with a residual plot

lts01   (lts01.xpl)
estimation of phonecal data set by OLS and LTS with graphical output

lts02   (lts02.xpl)
estimation of phonecal data set by LTS

lts03   (lts03.xpl)
estimation of stacklos data set by LTS

lts04   (lts04.xpl)
estimation of stacklos data set by LTS with a residual plot

mts01   (mts01.xpl)
calls the interactive quantlet for multiple time series analysis

pantlet   (pantlet.xpl)
application of panel data quantlets in XploRe to a macroeconomic data set

qr01   (qr01.xpl)
estimation of pullover data set by OLS

qr02   (qr02.xpl)
estimation of pullover data set by QR

qr03   (qr03.xpl)
median regression for nicfoo data

qr04   (qr04.xpl)
median regression, demonstration of robustness

qr05   (qr05.xpl)
median regression, demonstration of nonrobustness with respect to leverage points

qr06   (qr06.xpl)
regression rank score test

qr07   (qr07.xpl)
OLS and QR for nicfoo data shows five regression curves for tau=0.1,...,0.9 and one for OLS

qr08   (qr08.xpl)
median regression for nicfoo data, confidence intervals

rkalm01   (rkalm01.xpl)
simulates and plots data from contaminated multivariate normal distribution

rkalm02   (rkalm02.xpl)
shows effects of additive outliers on Kalman filter

rkalm03   (rkalm03.xpl)
shows effect of innovation outliers on Kalman filter

rkalm04   (rkalm04.xpl)
compares the classical Kalman filter and rLS filter

rkalm05   (rkalm05.xpl)
compares classical Kalman filter and rLS filter for simulated data with 10% of additive outliers

rkalm06   (rkalm06.xpl)
Calculates classical Kalman filter and rLS filter for data without outliers

rkalm07   (rkalm07.xpl)
calculates classical Kalman filter and rIC filter for data with additive outliers

rkalm08   (rkalm08.xpl)
calculates classical Kalman filter and rIC filter for data with 10% of additive outliers

rkalm09   (rkalm09.xpl)
calculates classical Kalman filter and rIC filter for data without outliers

seq01   (seq01.xpl)
Estimates the parameters of Klein's model

seq02   (seq02.xpl)
Estimates model of european money demand


© MD*Tech - Method and Data Technologies, generated on 19.7.2000 .