GA GB GC GD GE GF GG GH GI GJ GK GL GM GN GO GP GQ GR GS GT GU GV GW GX GY GZ

- galambos
- calculates the density function of a Galambos copula.
- gamfit
- gamfit provides an interactive tool for fitting additive models
- gammaci
- auxiliary quantlet for cointegration
- gammain
- sets defaults for library gam
- gamopt
- defines a list with optional parameters in gam quantlets. 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 validation.
- gamout
- auxiliary quantlet, creates a nice output for GAM.
- gamtest
- auxiliary quantlet, tests all quantlets of gam.lib (listed in See_also)
- garchest
- estimates a GARCH process with mean zero by QMLE
- garchnegdensder
- auxiliary quantlet for garchest
- garchneglikelihood
- auxiliary quantlet for garchest
- garchneglikelihoodder
- auxiliary quantlet for garchest
- garchneglikelihoodmat
- auxiliary quantlet for garchest
- GarmanKohlhagen
- calculates option prices using the Garman-Kohlhagen formula for European currency options.
- gasmregx
- calculates the Gasser-Mueller estimator using quartic kernel
- gasmregxb
- calculates the Gasser-Mueller estimator using quartic boundary kernel
- gau
- gau computes the (multivariate) Gaussian kernel
- gauder
- gauder evaluates derivatives of the Gaussian kernel rescaled by a bandwidth h, to be used for density estimation bandwidth selection.
- GaussLegendre
- abscissas and weights of the Gauss-Legendre n-point quadrature.
- genar
- generates autoregressive processes
- genarch
- generates a time series e_t=u_t*s_t, where u_t is standard normal distributed and the variances s^2_t follow the GARCH process s^2_t = a_0 + a(B)e^2_t + b(B)s^2_t Here, B denotes the backshift (or lag) operator. You have to deliver the coefficient vectors a and b and the length T of t
- genarma
- generates an autoregressive moving average process (ARMA) in deviations from the mean form y_t = a(B)y_t + eps_t + b(B)eps_t B denotes the backshift (or lag) operator. You have to deliver the AR coefficients vector a, the MA coefficients vector b and the (T x 1) white noise series eps. Th
- genbil
- generates the bilinear process x that has the following form x_t = phi(B)x_t + e_t + theta(B)e_t + sum sum c_(i,j)x_(t-i)e_(t-j) B denotes the backshift (or lag) operator. The AR polynom phi(B) has p coefficients and the MA polynom theta(B) has q coefficients. The first sum of the double sum goes
- genegarch
- generates EGARCH(p,q) with Gaussian errors
- genexpar
- generates the amplitude-dependent exponential AR (EXPAR) process x that has the following form x_t = a(B)x_t + exp{-delta x^2_(t-thrlag)}b(B)x_t + e_t B is the backshift (or lag) operator. The coefficient delta must be positive. The lag polynoms a(B) and b(B) must have the same order. e_t is a se
- 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 pa
- gennet
- generates interactively a feedforward network
- gennet2
- generates interactively a feedforward network
- gennorm
- Generates observations from a multivariate normal distribution with given mean vector and covariance matrix.
- gentar
- generates the threshold AR (TAR) process x that has the following form x_t = sum I{x_(t-thrlag) in (k_(i-1),k_i]}[phi_i(B)x_t]+e_t The sum goes from i=1 to nr (the number of threshold regions). I{} is an indicator function that takes the value 1 if the specified lagged value of x lies in the inte
- genvub
- genvub computes the volume of unit ball from dimension 1 up to 15 and put the results as global
- getbasismatrix
- auxiliary quantlet for createfdbasis, computes the basis matrix evaluated at arguments in evalarg associated with basisfd object.
- getdata
- Collects certain data from a plot. The dataset must be shown in the plot using show or adddata.
- getenv
- getenv reads the content of an environment variable set by the program or by the ini-file.
- getglobal
- getglobal reads a global variable
- getgopt
- Gets the layout of a plot. It is usually used to copy some of the layout components from one plot to another one.
- getlocalnow
- getlocalnow returns the current date and time with correction for the time zone, daylight savings and so on. The corrections are machine dependend.
- getnow
- getnow returns the current date and time in Greenwich time.
- gFourierInversion
- is a generic function that approximates the density of a distribution function by numerically inverting its characteristic function.
- 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 quantlet 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
- gkalarray
- This auxiliary quantlet sets the matrices for a time variable state space model.
- gkalfilter
- Calculates a filtered time series for a state space model (uni- or multivariate) with time variable system matrices using the Kalman filter. Furthermore, gkalfilter gives the value of the log likelihood function.
- gkallag
- Calculates covariance matrices for the smoothed series of a state space model (uni- or multivariate) with one lag. The quantlet gkallag needs a pre-run of gkalfilter. The state space model has the form (for the notation, see Harvey 1989): State equation alpha_t = c_t + T_t alpha_t-1 + e^s_t M
- gkalresiduals
- Calculates the innovations v_t and the standardized v^s_t residuals for a state space form that is estimated with the Kalman filter. As input, the output from the Kalman filter is needed. See the help to gkalfilter or the tutorial for a thorough discussion of the model.
- gkalsmoother
- calculates a smoothed time series for a state space model (uni- or multivariate) using the Kalman smoother. The quantlet gkalsmoother needs a pre-run of gkalfilter.
- 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 routine 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 routine offers a convenient interface for GLM estimation. A check of the data is performed.
- glmfit
- helper function 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 va
- 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 functions. 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 functions 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 a positive definite covariance matrix 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 routine 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 routine 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 gplmes
- gplmest
- gplmest fits a generalized partially linear model E[y|x,t] = G(x*b + m(t)). This routine 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 functions. 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 routines.
- 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 quantlets of the graphic library.
- grash
- Generates an averaged shifted histogram.
- graxes
- Generates axes with descriptions. Number of options is limited to 19 and unrecognized options are ignored
- graxes3d
- Generates 3-dimensional axes with descriptions.
- graxesgetval
- Auxiliary quantlet for reading the options of graxes.
- grbar
- generates a barchart.
- grbinomial
- generates a graphical object which represents the probability function of the 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 interval [Q_25-3*IQR, Q_75+3*IQR] will be plotted as crosses, outliers outside the interval [Q_25-1.5*IQR, Q_75+1.5*IQR] will be plotted as circles.
- grboxcl
- generates a boxplot of classified data with mean line and median line. Outliers outside the interval [Q_25-3*IQR, Q_75+3*IQR] will be plotted as crosses, outliers ouside the interval [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.
- grboxmeancl
- generates a boxplot of classified data with the mean line. The box borders are plus/minus one standard deviation from the mean line and the whiskers 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
- grboxmediancl
- generates a boxplot of classified data 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 the mean plus/minus two standard deviations in the norma
- grcandlesticks
- Generates the candlesticksplot for the stock price time series
- grcarttree
- generates the graphical objects for the regression/classification trees.
- 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 three-dimensional data set x
- grcontour3
- generates a contour plot from a 4-dimensional dataset x.
- grcoxcomb
- A coxcomb graph is a special pie chart. Its frequency is proportional to the area of the corresponding segment and the angles of the segments are all equal. Consequently, the frequency is proportional to the square of the radius of the segment.
- grcube
- Generates a 3-D cube with labels at the axes and grids on the borders, surrounding a 3-dimensional dataset.
- grdot
- Generates a dotplot.
- grdotcl
- generates a dotplot for classified data.
- grdotcl2
- generates a dotplot for classified data.
- grdotd
- Generates a dotplot as a density plot.
- grdotdcl
- generates a dotplot for classified data as a density plot.
- grdotdcl2
- generates a dotplot for classified data as a density plot.
- grdotdl
- Generates a dotplot as a density line.
- grdotdlcl
- generates a dotplot for classified data as a density line.
- grdotdlcl2
- generates a dotplot for classified data as a density line.
- greeks
- calculates or displays the different sensitivities (the so called greeks) which are used for trading with options.
- greeksaux
- auxiliary quantlet for greeks
- grface
- calculates Flury faces
- grfd
- creates graphical object from functional object fd
- grfdacorr
- creates a graphical object with corr surface
- grfdacov
- creates a graphical object with cov surface
- grfdavar
- creates a graphical object from the variance function of a functional object fd
- grgrid2
- creates a grid that encloses the given data. The grid will be drawn in light grey, if the optional color is not given.
- grhist
- Generates a histogram from the data.
- grhistcl
- generates a histogram from classified 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.
- grITTcrr
- generates a trinomial tree built from the standard CRR tree and describes it with the given values.
- grITTspd
- generates a state price density of an implied trinomial tree
- grITTstsp
- generates the state space of an implied trinomial tree.
- 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.
- grppn
- generates a probability-probability plot to compare a variable with a normal distribution.
- grppu
- generates a probability-probability plot to compare a variable with a uniform distribution.
- grqq
- generates a quantile-quantile plot to compare the distributions of 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.
- grrotate
- Rotates a graphical object by an arbitrary angle
- grscale
- scales a graphical object
- grspleplot
- grspleplot generates a graphic-object with spread and level plot
- grstar
- Generates a star diagram.
- grstree
- generates a survival tree
- grstreearrow
- auxiliary quantlet for grstree - generates the arrows in the survival tree
- grstreebox
- auxiliary quantlet for grstree - generates the boxes in the survival tree
- grstreecircle
- an auxiliary quantlet for grstree - generates the circles in the survival tree
- grsunflower
- Generates a sunflower plot.
- grsurface
- generates a surface plot from a 3-dimensional dataset.
- grsurfacecol
- generates a surface plot from a 3-dimensional dataset, with different color-levels depending on z-axis.
- grxline
- Generates a vertical line as a graphical object.
- gryline
- Generates a horizontal line as a graphical object.
- gumbel
- calculates the density function of a Gumbel Extreme Value Copula.
- gumbelII
- calculates the density function of a Gumbel II Extreme Value Copula.

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