
| | 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.
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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
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