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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 |.
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leafnum |
Gives the number of leaves (terminal nodes) in a
regression tree.
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lgamma |
lgamma computes logarithm of the gamma function.
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lgenci |
auxiliary macro for cointegration
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library |
library loads an xplore library
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line |
Convenient function for plotting results. Similar
to plot but uses lines instead.
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linreg |
linreg computes the Generalized Least Squares estimate for
the coefficients of a linear model.
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linregbs |
linregbs computes a backward elimination of a multiple
linear regression model.
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linregfs |
linregfs computes a simple forward selection for a
multiple linear regression model.
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linregfs2 |
linregfs2 computes a forward selection for a multiple
linear regression model.
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linregopt |
sets optional parameters for linregbs, linregfs2 and
linregstep
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linregres |
linregres computes some residual analysis for a linear
regression.
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linregstep |
linregstep computes a stepwise regression for a multiple
linear regression model.
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list |
list generates lists from given objects. If an object is temporary the name of the component is el<position>, otherwise the name of the object at this position.
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lo |
Calculation of the Lo statistic for long-range dependence.
The first argument of the quantlet is the series, the second
optional argument is the vector of truncation lags of the
autocorrelation consistent variance estimator. If the second
optional argument is missing, the vector of truncation lags
is set to m = 5, 10, 25, 50. The quantlet returns the estimated
statistic with its corresponding order. If the estimated statistic
is outside the interval (0.809, 1.862), which is the 95 percent
confidence interval for no long-memory,
a star symbol * is displayed in the third column. The other
critical values are in Lo's paper.
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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 function is the series. The second optional
argument is the vector of bandwidth, i.e., the parameter specifying
the number of harmonic frequencies around zero to be considered.
By default, the macro uses the automatic bandwidth given in Lobato and
Robinson. If the user provides his own vector of bandwidths, then the
function returns the value of the test for each component of the bandwidth vector.
If the value of the test is in the lower tail of the standard
normal distribution, the null hypothesis of I(0) is rejected against the
alternative that the series displays long-memory. If the value of the
test is in the upper tail of the standard normal distribution, the null
hypothesis I(0) is rejected against the alternative that the series is
antipersistent.
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locpol |
locpol computes the local polynomial estimator.
It is using the quartic kernel.
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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.
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log |
log returns the natural logarithm of the elements of an array.
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log10 |
log10 returns the logarithm base 10 of the elements of an array.
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log1p |
log1p computes the natural logarithm of (1+x) accurately even for tiny x.
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logarithmic |
performs a logarithmic transformation of the
selected variables in ISTA. The transformed variables can
replace the original ones or can be appended on the end of
data.x. The type is set automatically to continuous.
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logfile |
If a command was typed in the command line of the input window and
<Enter> was pressed then the command is written to the logfile.
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logit |
performs a logit (log((x/(1-x))) transformation of the
selected variables in ISTA. The transformed variables can
replace the original ones or can be appended on the end of
data.x. The type is set automatically to continuous.
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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.
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lowess |
lowess computes the robust locally weighted regression. Fitted values
are computed at each of the given values x.
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lpderest |
estimates the q-th derivative of a regression
function using local polynomial kernel regression.
The computation uses WARPing.
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lpderrot |
determines a rule-of-thumb bandwidth for univariate
local polynomial derivatives estimation using the
Quartic kernel.
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lpderxest |
estimates the q-th derivative of a regression
function using local polynomial kernel regression
with Quartic kernel.
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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.
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lpregest |
estimates a regression function using
local polynomial kernel regression.
The computation uses WARPing.
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lpregrot |
determines a rule-of-thumb bandwidth for univariate
local polynomial kernel regression using the
Quartic kernel.
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lpregxest |
estimates a univariate regression function using
local polynomial kernel regression with
Quartic kernel.
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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
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lregestp |
estimates a multivariate regression function using
local polynomial kernel regression. The computation
uses WARPing.
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lregxestp |
estimates a multivariate regression function using
local polynomial kernel regression with
Quartic kernel.
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lrseev |
LRS estimator for EV model
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ludecomp |
ludecomp computes the lu decomposition of a matrix.
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lvtest |
This quantlet tests for significance of a subset or of the whole set
of continuous regresssors in a nonparametric regression.
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