gamfit | gamfit provides an interactive tool for fitting additive models |
gammaci | auxiliary quantlet for cointegration |
gammain | sets defaults for library gam |
gamopt | gamopt defines a list with optional parameters in gam macros. The list is either created or new options are appended to an existing list. Note that gamopt does accept _any_ values for the parameters without validity. |
gamout | creates a nice output for GAM. ! auxiliary macro ! |
gamtest | tests all abovementioned macros of gam.lib |
gau | gau computes the gaussian kernel, multivariate |
gauder | gauder evaluates derivatives of the Gaussian kernel rescaled by a bandwidth h, to be used for density estimation bandwidth selection. |
genar | genar generates an autoregressive process. |
genarch | generates a GARCH process with Gaussian innovations |
genarma | generates an autoregressive moving average process with mean zero |
genbil | generates a bilinear process x(t)=sum phi(i)x(t-i) + sum theta(j)e(t-j) + sum sum gamma(i,j)x(t-i)e(t-j) |
genexpar | generates an exponential AR process |
genglm | genglm generates data from a GLM model. |
genmultlo | genmultlo generates data according to a multinomial logit model with P( Y = j | Xa , Xi) proportional to exp( Xa * ba + Xi * bi[j] ). Here, Xi denotes the part of the explanatory variables which merely depends on the individuals, Xa covers variables which may vary with the alternatives j. Either part, Xa or Xi, can be omitted. |
gennet | generates interactively a feedforward network |
gennorm | Generates observations from a multivariate normal distribution with given mean vector and covariance matrix. |
gentar | generates a Threshold AR process |
genvub | genvub computes the volume of unit ball from dimension 1 up to 15 and put the results as global |
getdata |
getdata gets a data from a plot.
The data set must be previous shown in this plot using show oder adddata. |
getenv | getenv reads the content of an environment variables set by the program or by the ini-file. |
getglobal |
getglobal reads a global variable
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getgopt |
getgopt gets the layout of a plot. It is usually used to copy some of all layout components from one plot to another one.
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getlocalnow | getlocalnow returns the actual date and time with correction for the time zone, daylight savings and so on. The corrections are machine dependend. |
getnow | getnow returns the actual date and time in Greenwich time. |
getxgobiinfo | |
gform | Supporting Quantlet for cartsplit |
gintest | estimation of the univariate additive functions in a separable generalized additive model using Nad.Watson, local linear or local quadratic |
gintestpl | gintestpl fits an additive generalized partially linear model E[y|x,t] = G(x*b + m(t)). This macro offers a convenient interface for GPLM estimation. A preparation of data is performed (inclusive sorting). |
ginv | Calculates a pseudo-inverse of x, such that x*ginv(x)*x = x. |
givenrot | Decomposes an orthonormal matrix into a set of rotations by Givens rotation |
glmbackward | glmbackward performs a backward model selection by searching the best of all subset models w.r.t. the AIC or BIC criterion. Optionally, a number of columns can be given, which are always included in the submodels. |
glmcore | fits a generalized linear model E[y|x] = G(x*b). This is the core macro for GLM estimation. It assumes that all input variables are given in the right manner. No preparation of data is performed. A more convenient way to estimate a GLM is to call the function glmest. |
glmdiagh | glmdiagh calculates the diagonal elements of the 'hat' matrix |
glmest | glmest fits a generalized linear model E[y|x] = G(x*b). This macro offers a convenient interface for GLM estimation. A check of the data is performed. |
glmfit | helper macro for doglm. |
glmforward | glmforward performs a forward model selection by searching the best of all subset models w.r.t. the AIC or BIC criterion. Optionally, a number of columns can be given, which are always included in the submodels. |
glminit | glminit checks the validity of input and performs the initial calculations for an GLM fit. The output is ready to be used with glmcore. |
glminvlink | glminvlink computes the inverse link function. |
glmlink | glmlink computes the link function. |
glmll | glmll computes the individual log-likelihood. |
glmlld | glmlld computes the first and second derivative of the individual log-likelihood in dependence of the linear index eta and y. |
glmlrtest | glmlrtest performs a likelihood ratio test of two nested GLM. |
glmmain | sets defaults for library glm. |
glmmultlo | glmmultlo fits a multinomial/conditional logit model where the response Y is multinomial distributed. This means, P( Y = j | Xa , Xi) is proportional to exp( Xa * ba + Xi * bi[j] ). Here, Xi denotes that part of the explanatory variables which merely depends on the individuals and Xa covers variables which may vary with the alternatives j. Either part, Xa or Xi, can be omitted. |
glmmultshape | reshapes data from panel format to matrix format and vice versa. The matrix format is needed for glmmultlo. |
glmopt | glmopt defines a list with optional parameters in glm macros. The list is either created or new options are appended to an existing list. Note that glmopt does accept _any_ values for the parameters without validity. |
glmout | glmout creates a nice output display for GLM. |
glmplot | glmplot creates a display and plots for a one-dimensional explanatory variable: the distribution, a scatterplot of the marginal influence versus the response and a scatterplot of the variabel versus the response. |
glmscatter | glmscatter computes a scatterplot to explain the marginal influence of a variable on the response. |
glmselect | glmselect performs a model selection by searching the best of all subset models w.r.t. the AIC or BIC criterion. Optionally a number of columns can be given, which are always included in the submodels. |
glmstat | glmstat provides some statistics for a fitted GLM. |
glmtest | executes some tests for the macros defined in glm.lib. Is invoked by vertestl(). |
gls | Computes the Generalized Least Squares estimate for the coefficients of a linear model when the errors have as covariance matrix sigma^2 * om. |
gp1me | gp1me evaluates the mean excess function of the Pareto (GP1) distribution with shape parameter alpha for all elements of a vector. |
gph | Estimation of the degree of long memory of a time series by using a log-periodogram regression |
gplmbootstraptest | Bootstrap test for comparing GLM vs. GPLM. The hypothesis E[y|x,t] = G(x*b + t*g + c) is tested against the alternative E[y|x,t] = G(x*b + m(t)). This macro offers a convenient interface for GPLM estimation and testing. A preparation of data is performed (inclusive sorting). |
gplmcore | gplmcore fits a generalized partially linear model E(y|x,t) = G(x*b + m(t)). This is the core macro for GPLM estimation. It assumes that all input variables are given in the right manner. No preparation of data is performed. A more convenient way to estimate a GPLM is to call the function gplmest. |
gplmest | gplmest fits a generalized partially linear model E[y|x,t] = G(x*b + m(t)). This macro offers a convenient interface for GPLM estimation. A preparation of data is performed (inclusive sorting). |
gplminit | gplminit checks the validity of input and performs the initial calculations for an GPLM fit (inclusive sorting). The output is ready to be used with gplmcore. |
gplmmain | loads everything necessary for library gplm. |
gplmopt | gplmopt defines a list with optional parameters in gplm macros. The list is either created or new options are appended to an existing list. Note that gplmopt does accept _any_ values for the parameters without validity. |
gplmout | gplmout creates a nice output display for gplm. |
gplmstat | gplmstat provides some statistics for a fitted GPLM. |
gplmtest | gplmtest verifies the GPLM macros. |
gpme | gpme evaluates the mean excess function of the GP distribution with shape parameter gamma for all elements of a vector. |
gpplot | returns the Grassberger-Procaccia plot for time series |
gpsigmaest | estimator for scale parameter within GP models |
grandrews | Generates an Andrews plot. |
graphicmain | Generates graphical constants and loads all libraries necessary for the graphics. |
graphictest | Tests the macros of the graphic library. |
grash | Generates an averaged shifted histogram. |
graxes3d | Generates a 3-D axes with descriptions. |
grbar | Generates a barchart. |
grbinomial | generates a graphical object which represents the probability function of a binomial distribution B(n,p) |
grbiplot | Generates a graphical object containing the coordinates for the biplot of a given matrix. |
grbox | Generates a boxplot with mean line and median line. Outliers outside the intervall [Q_25-3*IQR, Q_75+3*IQR] will be plotted as crosses, outliers ouside the intervall [Q_25-1.5*IQR, Q_75+1.5*IQR] will be plotted as circles. |
grboxgrouped | Generates a boxplot for grouped data with mean line (dotted) and median line (solid). |
grboxmean | Generates a boxplot with the mean line. The box borders are plus/minus one standard deviation of the mean line and the whiskers are plus/minus two standard deviations. |
grboxmedian | Generates a boxplot with the median line. The box borders are the percentiles which are equivalent to the mean plus/minus one standard deviation in the normal case (16% and 84% percentile) and the whiskers are equivalent to to the mean plus/minus two standard deviations in the normal case (2.5% and 97.5% percentile). |
grcart2 | produces the cut graphic for a CART tree. |
grcircle | Generates a circle or ellipse as a graphical object. The circle is centered at (0,0) and has the given radius. |
grcirclesector | Generates a sector of a circle. |
grcolorscheme | Returns a vector of rgb colors. |
grcontour2 | Generates a contour plot from a 3-dimensional dataset x. |
grcontour3 | generates a contour plot from a 4-dimensional dataset x. |
grcube | Generates a 3-D cube with labels at the axes surrounding a 3-dimensional dataset. |
grdot | Generates a dotplot. |
grdotd | Generates a dotplot as a density plot. |
grdotdl | Generates a dotplot as a density line. |
greeks | calculates and displays the different indices which are used for trading with options, in particular delta (the partial derivative of an option with respect to the price S of the underlying asset), gamma (2 x p .d.w.r.t. price S of underlying asset), eta (delta x S / option price), delta-K (p.d.w.r.t. exercise price K), vega (p.d.w.r.t. the volatility of the asset), theta (p.d.w.r.t. the time to expiration), rho (p.d.w.r.t. the domestic interest rate), rho-b (p.d. w.r.t. the costs of carry (in percent of the value of the underlying object)). |
grface | calculates Flury faces |
grhist | Generates a histogram from the data. |
grid | This command generates a grid with origin x and stepwidth h with respect to each dimension, n indicating the number of gridpoints in the respective dimension. |
grlinreg | Generates a graphical object which contains a linear regression line from the data. |
grlinreg2 | generates a graphical object which contains a linear regression plane from the data. The plane is computed on a rectangular grid with n^2 meshes. |
grmove | Moves a graphical object. |
groupcol | Decomposes a (color) vector into single groups. |
grpcp | Generates a parallel coordinates plot. |
grpie | Generates a pie chart from the data. |
grpp | generates a probability-probability-plot to compare two variables |
grppn | generates a probability-probability-plot to compare a variable with a normal distribution |
grqq | Generates a quantile-quantile-plot to compare two variables. |
grqqn | Generates a quantile-quantile-plot to compare a variable with a normal distribution. |
grqqu | Generates a quantile-quantile-plot to compare a variable with a uniform distribution. |
grrot | Rotates a graphical object. |
grscale | scales a graphical object |
grstar | Generates a star diagram. |
grsunflower | Generates a sunflower plot. |
grsurface | generates a surface plot from a 3-dimensional dataset. |
gruppenscatter | creates according the selected variables and group variables the appropriate parameters d, c, r and title to build the displays in showd for a scatterplot |
gruppenscatterp | creates according the selected variables the appropriate parameters d, c, r and title to build the displays in showd for a scatterplot for the saved variables after regression analysis (no group variable possible) |
gruppenvariable | creates according the selected variables and group variables the appropriate parameters d, c, r and title to build the displays in showd |
gruppenvariable2 | creates according the selected variables and group variables the appropriate parameters d, c, r and title to build the displays in showd for barcharts, boxplots, dotplots |
grxline | Generates a vertical line as a graphical object. |
gryline | Generates a horizontal line as a graphical object. |