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A B C D E F H J K L M N P Q R S T U V X
| QRMlib-package | This package provides R-language code to investigate concepts in a Quantitative Risk Management book for those users without access to S-Plus. |
| aggregateMonthlySeries | aggregateMonthlySeries() method |
| aggregateQuarterlySeries | aggregateQuarterlySeries() method |
| aggregateSignalSeries | aggregateSignalSeries() method |
| aggregateWeeklySeries | aggregateWeeklySeries() method |
| besselM3 | Modified Bessel Function of 3rd Kind |
| BetaDist | The Beta Distribution |
| BiDensPlot | Bivariate Density Plot |
| cac40 | CAC 40 Stock Market Index (France) as timeSeries object from January 1994 to March 25, 2004 |
| cac40.df | CAC 40 Stock Market Index (France) as dataframe object from anuary 1994 to March 25, 2004 |
| cal.beta | Calibrate Beta Mixture of Bernoullis |
| cal.claytonmix | Calibrate Mixture of Bernoullis Equivalent to Clayton Copula Model |
| cal.probitnorm | Calibrate Probitnormal Mixture of Bernoullis |
| claytonmix | Mixing Distribution on Unit Interval Yielding Clayton Copula Model |
| ConvertDFToTimeSeries | ConvertDFToTimeSeries() method |
| CovToCor | Covariance To Correlation Matrix |
| danish | Danish Data from January 1980 through December 1990 as timeSeries object |
| danish.df | Danish Data from January 1980 through December 1990 as data.frame object |
| dbeta | The Beta Distribution |
| dclaytonmix | Mixing Distribution on Unit Interval Yielding Clayton Copula Model |
| dcopula.AC | Archimedean Copula Density |
| dcopula.clayton | Bivariate Clayton Copula Density |
| dcopula.gauss | Gauss Copula Density |
| dcopula.gumbel | Bivariate Gumbel Copula Density |
| dcopula.t | t Copula Density |
| dGEV | Generalized Extreme Value Distribution |
| dghyp | Univariate Generalized Hyperbolic Distribution |
| dghypB | Univariate Generalized Hyperbolic Distribution B |
| dGPD | Generalized Pareto Distribution |
| dGumbel | Gumbel Distribution |
| DJ | Dow Jones 30 Stock Prices (timeSeries object) January 1991 to December 2000 |
| DJ.df | Dow Jones 30 Stock Prices (data.frame object) January 1991 to December 2000. The .df indicates the dataframe object. |
| dji | Dow Jones Index (timeSeries Object) January 2, 1980-March 25, 2004 |
| dji.df | Dow Jones Index (dataframe Object) January 2, 1980-March 25, 2004. The .df indicates the dataframe object. |
| dmghyp | Multivariate Generalized Hyperbolic Distribution |
| dmnorm | Multivariate Normal Density |
| dmt | Multivariate Student t Density |
| dprobitnorm | Probit-Normal Distribution |
| dsmghyp | Symmetric Multivariate Generalized Hyperbolic Distribution |
| edf | Empirical Distribution Function |
| EGIG | Estimate Moments of GIG Distribution |
| eigenmeth | Make Matrix Positive Definite |
| ElogGIG | Log Moment of GIG |
| EMupdate | EM Update Step for Generalized Hyperbolic Estimation |
| equicorr | Equicorrelation Matrix |
| ESnorm | Expected Shortfall for Normal Distribution |
| ESst | Expected Shortfall for Student t Distribution |
| extremalPP | Extremal Point Process |
| findthreshold | Find a Threshold |
| fit.AC | Fit Archimedean Copula |
| fit.Archcopula2d | Fit 2D Archimedean Copula |
| fit.binomial | Fit Binomial Distribution |
| fit.binomialBeta | Fit Beta-Binomial Distribution to defaults and obligors |
| fit.binomialLogitnorm | Fit Logitnormal-Binomial Distribution |
| fit.binomialProbitnorm | Fit Probitnormal-Binomial Distribution |
| fit.gausscopula | Fit Gauss Copula |
| fit.GEV | Fit Generalized Extreme Value Distribution |
| fit.GPD | Fit Generalized Pareto Model |
| fit.GPDb | Fit Generalized Pareto Model B |
| fit.mNH | Fit Multivariate NIG or Hyperbolic Distribution |
| fit.mst | Fit Multivariate Student t Distribution |
| fit.NH | Fit NIG or Hyperbolic Distribution |
| fit.norm | Fit Multivariate Normal |
| fit.POT | Peaks-over-Threshold Model |
| fit.seMPP | Fit Marked Self-Exciting Point Process |
| fit.sePP | Fit Self-Exciting Process |
| fit.st | Fit Student t Distribution |
| fit.tcopula | Fit t Copula |
| fit.tcopula.rank | Fit t Copula Using Rank Correlations |
| ftse100 | FTSE 100 Stock Market Index as timeSeries object |
| ftse100.df | FTSE 100 Stock Market Index as dataframe object |
| FXGBP.RAW | Sterling Exchange Rates as timeSeries object |
| FXGBP.RAW.df | Sterling Exchange Rates as data.frame object January 1987 to March 2004. The .df indicates the dataframe object. |
| hessb | Approximate Hessian Matrix |
| hillPlot | Create Hill Plot |
| hsi | Hang Seng Stock Market Index (timeSeries) |
| hsi.df | Hang Seng Stock Market Index (dataframe) January 1994 to March 2004 |
| jointnormalTest | Test of Multivariate Normality |
| Kendall | Kendall's Rank Correlation |
| kurtosisSPlus | S-Plus Version of Kurtosis which differs from the R-versions |
| lbeta | Log Beta Function |
| MardiaTest | Mardia's Tests of Multinormality |
| MCECM.Qfunc | Optimization Function for MCECM Fitting of GH |
| MCECMupdate | MCECM Update Step for Generalized Hyperbolic |
| MEplot | Sample Mean Excess Plot |
| mghyp | Multivariate Generalized Hyperbolic Distribution |
| mk.returns | Make Financial Return Data |
| momest | Moment Estimator of Default Probabilities |
| nasdaq | NASDAQ Stock Market Index (timeSeries object) January 3, 1994 to March 25, 2004 |
| nasdaq.df | NASDAQ Stock Market Index (data.frame object) January 3, 1994 to March 25, 2004 |
| nikkei | Nikkei Stock Market Index (timeSeries Object) January 4, 1994-March 25, 2004 |
| nikkei.df | Nikkei Stock Market Index (data.frame Object) January 4, 1994-March 25, 2004 |
| pbeta | The Beta Distribution |
| pclaytonmix | Mixing Distribution on Unit Interval Yielding Clayton Copula Model |
| Pconstruct | Assemble a Correlation Matrix for ML Copula Fitting |
| Pdeconstruct | Disassemble a Correlation Matrix for ML Copula Fitting |
| pGEV | Generalized Extreme Value Distribution |
| pGPD | Generalized Pareto Distribution |
| pGumbel | Gumbel Distribution |
| plot.MPP | Plot Marked Point Process |
| plot.PP | Plot Point Process |
| plot.sePP | Plot Self-Exciting Point Process |
| plotFittedGPDvsEmpiricalExcesses | Graphically Compare Empirical Distribution of Excesses and GPD Fit |
| plotMultiTS | Plot Multiple Time Series |
| plotTail | Tail Plot of GPD Model |
| pprobitnorm | Probit-Normal Distribution |
| probitnorm | Probit-Normal Distribution |
| profileLoadLibrary | Build .Rprofile File to Load QRM Library in QRMBook Workspace |
| psifunc | Psi or Digamma Function |
| qbeta | The Beta Distribution |
| qGEV | Generalized Extreme Value Distribution |
| qGPD | Generalized Pareto Distribution |
| qGumbel | Gumbel Distribution |
| QQplot | Generic Quantile-Quantile Plot |
| QRMBook-workspace | How to Build a QRMBook Workspace in R to Use QRMlib |
| QRMlib | This package provides R-language code to investigate concepts in a Quantitative Risk Management book for those users without access to S-Plus. |
| qst | Student's t Distribution (3 parameter) |
| rAC | Generate Archimedean Copula |
| rACp | Simulate a Generalized Archimedean Copula representing p factors |
| rBB9Mix | Mixture Distribution Yielding BB9 Copula |
| rbeta | The Beta Distribution |
| rbinomial.mixture | Sample Mixed Binomial Distribution |
| rclaytonmix | Mixing Distribution on Unit Interval Yielding Clayton Copula Model |
| rcopula.clayton | Clayton Copula Simulation |
| rcopula.frank | Frank Copula Simulation |
| rcopula.gauss | Gauss Copula Simulation |
| rcopula.gumbel | Gumbel Copula Simulation |
| rcopula.Gumbel2Gp | Gumbel Copula with Two-Group Structure |
| rcopula.GumbelNested | Gumbel Copula with Nested Structure |
| rcopula.t | t Copula Simulation |
| rFrankMix | Mixture Distribution Yielding Frank Copula |
| rGEV | Generalized Extreme Value Distribution |
| rghyp | Univariate Generalized Hyperbolic Distribution |
| rghypB | Univariate Generalized Hyperbolic Distribution B |
| rGIG | Generate Random Vector from Generalized Inverse Gaussian Distribution |
| rGPD | Generalized Pareto Distribution |
| rGumbel | Gumbel Distribution |
| RiskMeasures | Calculate Risk Measures from GPD Fit |
| rlogitnorm | Random Number Generation from Logit-Normal Distribution |
| rmghyp | Multivariate Generalized Hyperbolic Distribution |
| rmnorm | Multivariate Normal Random Sample |
| rmt | Multivariate t |
| rprobitnorm | Probit-Normal Distribution |
| rstable | Stable Distribution |
| rtcopulamix | Mixing Distribution on Unit Interval Yielding t Copula Model |
| seMPP.negloglik | Marked Self-Exciting Point Process Log-Likelihood |
| sePP.negloglik | Self-Exciting Point Process Log-Likelihood |
| showRM | Show Risk Measure Estimates on Tailplot |
| signalSeries | signalSeries object |
| smi | Swiss Market Index (timeSeries Object) November 9, 1990 to March 25, 2004 |
| smi.df | Swiss Market Index (dataframe Object) November 9, 1990 to March 25, 2004. The .df indicates the dataframe object. |
| sp500 | Standard and Poors 500 Index (timeSeries Object) January 2, 1990-March 25, 2004 |
| sp500.df | Standard and Poors 500 Index (data.frame Object) January 2, 1990-March 25, 2004 |
| spdata | Standard and Poors Default Data |
| spdata.df | Standard and Poors Default Data |
| spdata.raw | Standard and Poors Default Data (timeSeries object) |
| spdata.raw.df | Standard and Poors Default Data (Dataframe) |
| Spearman | Spearman's Rank Correlation |
| stationary.sePP | Stationarity of Self-Exciting Model |
| storeDataInWorkspace | How to Store Data in a QRMBook Workspace |
| symmetrize | Ensure Symmetric Matrix |
| timeSeriesClass | timeSeries Objects in R |
| TimeSeriesClassRMetrics | timeSeries Class and Methods |
| unmark | Unmark Point Process |
| volfunction | Self-Excitement Function |
| xdax | Xetra DAX German Index (timeSeries Object) January 3, 1994-March 25, 2004 |
| xdax.df | Xetra DAX German Index (timeSeries Object) January 3, 1994-March 25, 2004 |
| xiplot | GPD Shape Parameter Plot |