Keywords - Function Groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

metrics

adedis
computes estimates of the slope coefficients in a single index model. The coefficents of the continuous variables are estimated by (an average of) dwade (density-weighted average derivative) estimates. The coefficients of the discrete explanatory variables are estimated by the method proposed in Ho
adedisdewade
auxiliary quantlet for adedis, dwade with the fourth order kernel
adedisrfunction
auxiliary quantlet for adedis, computes variance of beta
adeind
indirect average derivative estimation using binning
adeslp
slope estimation of average derivatives using binning
andrews
andrews calculates the semiparametric estimator proposed by Andrews and Schafgans (1994) of the intercept coefficients of the outcome equation in a sample selection model.
deahull
returns the DEA (Data Envelopment Analysis) input efficiency score and efficient level of inputs for each DMU (Decision making unit)
dpls
calculates latent variables, weights, loadings and path coefficients with dynamic partial least squares algorithm
dwade
dwade estimation of the density weighted average derivatives
fdhull
returns the FDH (free disposal hull) efficiency scores for each DMU (Decision Making Unit)
heckman
2-step estimation of a regression equation in the presence of self-selection. Selection rule is of the probit type (hence, this is a Type 2 Tobit Model in chapter 10 of Amemiya's Advanced Econometrics).
hhmult
hhmult calculates the H-H statistic to jointly test the specification of the link functions of a polychotomous response model (such as the conditional logit model or the multinomial logit model)
hhtest
hhtest calculates the H-H statistic to test the specification of the link function of a generalized linear model (such as the logit or probit model), assuming the index is correctly specified.
lts
Computes the least trimmed squares estimate for the coefficients of a linear model.
makedesign
generates interactively design matrices for the dpls quantlet (dynamic partial least squares algorithm)
metricsmain
loads the quantlibs needed by the quantlets in the metrics quantlib
metricstest
tests the integrity of the metrics library. It is invoked by vertest().
MIregest
Estimates a Multi Index model by finding the orthogonal transformation matrix B by the MAVE and the OPG method. The model has the following form: y = g(B*x) + error, where B*x represents the Multi Index.
ndw
auxiliary quantlet for adedis. It defines the Nadaraya-Watson estimate of the link as a function of the (estimated) index of continuous explanatory variables. In adedis, the quantlet simpsonint is used to integrate over the function.
newadeslp
slope estimation of average derivatives
powell
powell calculates the semiparametric estimator proposed by Powell (1987) of the slope coefficients of the outcome equation in a sample selection model.
redun
calculates a single redundance and a redundance vector for dpls quantlet as a measure of goodness.
rqfit
Performs quantile regression of y on x using the original simplex approach of Barrodale-Roberts/Koenker-d'Orey.
rrstest
Computes the regression rankscore test of a linear hypothesis based on the dual quantile regression process. It tests the hypothesis that b1 = 0 in the quantile regression model y = x0'b0 + x1'b1 + u. Test statistic is asymptotically Chi-squared with rank(x1) degrees of freedom.
select
select calculates semiparametric estimates of the intercept and slope coefficients in the "outcome" or "level" equation of a self-selection model. It is the second step of the two-step estimator of these models. It combines the procedures in the quantlets powell (slope estimator) and andrews (inter
seq
Estimates a simultaneous equations model by 3-stage least squares
sir
Calculates the effective dimension-reduction (edr) directions by Sliced Inverse Regression (Li, 1991)
sir1
the taylored Sliced Inverse Regression method for the "sssm" quantlet.
sir2
Calculates the effective dimension-reduction (edr) directions by Sliced Inverse Regression II (Li, 1991)
sssm
computes the estimates of the slope vectors in the outcome equation and in the selection equation for a semiparametric sample selection model (SSSM).
sur
Estimates a seemingly unrelated regression system by feasible generalized least squares
tobit
2-step estimation of a Tobit model
trimper
trims a given percentage of a (binned) data matrix
wtsder
computes the weights for derivative estimation for the use with the quatric kernel in the context of binning

Keywords - Function Groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

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