LA LB LC LD LE LF LG LH LI LJ LK LL LM LN LO LP LQ LR LS LT LU LV LW LX LY LZ

- l1fit
- Estimate L1 regression (least absolute deviation regression) of y on x.
- l1line
- l1line computes the least absolute deviation line from scatterplot data. It gives the estimate b0 and b1 that minimizes sum_i=1,n |y_i - b0 - b1 x_i |.
- lab2rgb
- converts an L*a*b* colour vector into an RGB vector.
- levene
- levene runs Levene-test
- levf
- returns the limited expected value.
- lgamma
- lgamma computes logarithm of the gamma function.
- lgenci
- auxiliary quantlet for cointegration
- library
- library loads an xplore library
- linapprox
- interpolates linearly from given discretized one-dimensional functions on the same grid.
- line
- convenient function for plotting results. Similar to plot but draws lines connecting the points.
- linreg
- Computes the Generalized Least Squares estimate for the coefficients of a linear model.
- linregbs
- linregbs computes a backward elimination of a multiple linear regression model.
- linregfs
- linregfs computes a simple forward selection for a multiple linear regression model.
- linregfs2
- computes a forward selection for a multiple linear regression model.
- linregopt
- sets optional parameters for linregbs, linregfs2 and linregstep.
- linregres
- linregres computes some residual analysis for a linear regression.
- linregstep
- linregstep computes a stepwise regression for a multiple linear regression model.
- list
- list generates lists from given objects. If an object is temporary the name of the component is el
, otherwise the name of the object at this position. - lms
- Computes the least median of squares estimate for the coefficients of a linear model.
- lo
- Calculation of the Lo statistic for long-range dependence.
- lobrob
- Semiparametric test for I(0) of a time series against fractional alternatives, i.e., long-memory and antipersistence. The test is semiparametric in the sense that it does not depend on a specific parametric form of the spectrum in the neighborhood of the zero frequency. The first argument of the fu
- lochomest
- calls the quantlet "lochomtest" and performs the estimation of the volatility for the whole time series at regular grid points.
- lochomtest
- computes the most recent interval of homogeneity of the volatilities of financial time series data and the local mean relative to this interval.
- locpol
- locpol computes the local polynomial estimator. It is using the quartic kernel.
- locpoldis
- locpoldis computes the local polynomial estimator without mixed terms but allows for including a linear part in the regression model. It is using the quartic kernel.
- locpolex
- computes the local polynomial estimator with an arbitrary kernel.
- log
- log returns the natural logarithm of the elements of an array.
- log10
- log10 returns the logarithm base 10 of the elements of an array.
- log1p
- log1p computes the natural logarithm of (1+x) accurately even for tiny x.
- logfile
- If a command was typed in the command line of the input window and
was pressed then the command is written to the logfile. - loglikBurr
- auxiliary function for estBurr.
- loglikgamma
- auxiliary quantlet for estgamma.
- loglikmixexp
- auxiliary quantlet for estmixexp.
- loglikPareto
- auxiliary quantlet for estPareto.
- loglikWeibull
- auxiliary quantlet for estWeibull
- logsplinefit
- estimates density function using splines
- logsplinesummary
- summarizes the results of estimation of quantlet logsplinefit
- looreg
- computes the Nadaraya-Watson leave-one-out estimator without binning using the quartic kernel. Prior to estimation, looreg sorts the data. The sorted data, along with the sorted leave-one-out regression estimates, are returned as an output.
- lorenz
- calculates the measures of concentration of Gini and Herfindahl
- lowdiscrepancy
- computes the first n d-dimensional sequence elements of the low-discrepancy generator seqnum.
- lowess
- lowess computes the robust locally weighted regression. Fitted values are computed at each of the given values x.
- lpderest
- estimates the q-th derivative of a regression function using local polynomial kernel regression. The computation uses WARPing.
- lpderrot
- determines a rule-of-thumb bandwidth for univariate local polynomial derivatives estimation using the Quartic kernel.
- lpderxest
- estimates the q-th derivative of a regression function using local polynomial kernel regression with Quartic kernel.
- lpdist
- computes the so-called Lp-distances between the rows of a data matrix. In the case p=1 (absolute metric) or p=2 (Euclidean metric) one should favour the function DISTANCE.
- lplocband
- Estimates the derivative of a regression function (including the 0th derivative) by local polynomial fits on a grid. This quantlet can be used for univariate or multivariate regression estimation.
- lpregest
- estimates a regression function using local polynomial kernel regression. The computation uses WARPing.
- lpregrot
- determines a rule-of-thumb bandwidth for univariate local polynomial kernel regression using the Quartic kernel.
- lpregxest
- estimates a univariate regression function using local polynomial kernel regression with Quartic kernel.
- lprotint
- lprotint computes the integral of the (p+1)st derivative of a polynomial of order (p+3), this function is used to find rule-of-thumb bandwidth for local polynomial regression and derivative estimation
- lregestp
- estimates a multivariate regression function using local linear kernel regression. The computation uses WARPing.
- lregxestp
- estimates a multivariate regression function using local linear kernel regression with Quartic kernel.
- lrseev
- LRS estimator for an Extreme Value model
- lsdcheckfit
- auxiliary quantlet for logspline density estimation - checks if list "fit" is compatible with output of logsplinefit quantlet
- lts
- Computes the least trimmed squares estimate for the coefficients of a linear model.
- ludecomp
- computes the LU decomposition of a square matrix, ; where L represents the lower ; and U the upper triangular matrix.
- lvtest
- This quantlet tests for significance of a subset or of the whole set of continuous regresssors in a nonparametric regression.

(C) MD*TECH Method and Data Technologies, 05.02.2006 | Impressum |