Man pages for thiyangt/fformpp
Feature-based FORecast Model Performance Prediction
| array2list | Convert an array(or matrix) to a list |
| aT.x.DvecSigma4beta.inv | <description> |
| block.diag | Block diagonal matrix. |
| close.all | Close all graphics devices. |
| combination_forecast | Function to generate combination forecast |
| convert.densParams | Convert the parameters corresponding to different... |
| data.partition | Partition data index for cross validation. |
| delta.K | Gradient for a diagonal matrix. |
| delta.vecPartiSigma4beta.inv | This is the gradient for a single partition of beta's... |
| delta.xi | Gradient with respect to the knots locations. |
| DensGradHess | A collection of gradient and Hessian for the log form of... |
| density_prior | Densities for priors |
| deriv_prior | Gradient for priors |
| DGP | DATA GENERATING PROCESSES |
| DGP.surface | DGP Surface nested |
| diwishart | ##' Density for the inverse wishart distribution |
| d.matrix | Design matrix for splines |
| dmixnorm | Density for normal mixtures |
| dmixnorm.ts | The conditional density for AR-type mixture of normals |
| dot-ls.objects | List the object size Modified from Dirk Eddelbuettel's... |
| dsplitt | Split student-t distribution |
| fcast_m1 | fcast_m1 |
| features.df | features.df |
| features.df.m1 | features.df.m1 |
| fformpp.model | fformpp.model |
| FitDiagnosis | Diagnosis if the spline model |
| FitDiagnosis.hwang | Diagnosis if the spline model |
| fit_fformpp | Function to fit Efficient Bayesian Surface Regression Models. |
| foldMat | Fold a matrix |
| forecast.error | forecast.error |
| forecast.error.m1 | forecast.error.m1 |
| ghypergeo | The generalized hypergeometric function pFq. |
| glm_logpost | The conditional and joint log posterior function |
| glogit | logit transformation |
| grapes-d-times-grapes | Fast matrix algebra with diagonal matrices. |
| grid2 | Add grids on plot |
| harmonic | Harmonic number |
| hessApprox | Numerical approximation of Hessian |
| hessian_approx | Numerical approximation of hessian matrix. |
| ibeta | Incomplete beta function |
| idx.b2beta | Make indices from b to beta. |
| idx.beta2b | Convert indices from beta to b |
| individual_forecast | Function to generate forecasts from minimum error |
| ineff | Inefficiency factor |
| is.singular | Check if a square matrix is computational singular |
| knots_check_boundary | Description |
| knots_list2mat | Convert list of knots into a n-by-1 matrix. |
| knots_mat2list | convert the knots matrix into the knots list |
| knots_subsetsIdx | This function is to find the locations of subsets in the... |
| KStepNewtonMove | This is the simple Newton move for spline models without... |
| linear_IWishart | Calculate the posterior df and location matrix V from the... |
| locate.knots | Locate knots in a m-space using Villani(2009)'s algorithm. |
| LogPredScore | This is the LPDS |
| log_prior | logarithm density for priors |
| make.knots | Locate the knots in m-space. |
| make.knotsPriVar | set the prior variance of the knots. |
| make_stepsize | Make step size for SGLD |
| Mat.delta.xi | <description> |
| Mat.x.AT.k.I.x.K.x.delta.knots | <description> |
| Mat.x.delta.vecSigma4beta.inv | Compute a matrix to pre-multiply the gradient for vec beta's... |
| Mat.x.DvecA.k.P_stp1 | Perform a dense matrix multiplying by Dev[vec[A K_qi,qi) |
| Mat.x.DvecA.k.P_stp2 | <description> |
| Mat.x.DvecA.k.XTX_stp1 | Perform a dense matrix multiplying by Dev[vec[A K_qi,qi) |
| mesh.grid | Same as expand.grid function but return a matrix. |
| MHPropMain_rw | The Main file for Metropolis–Hastings algorithm |
| MHPropMain_sgld | The Main file for MCMC algorithm. |
| MHPropWithIWishart | Random walk Metropolis–Hastings algorithm for Sigma |
| MHPropWithKStepNewton | Metropolis–Hastings algorithm with K-step Newton method for... |
| mseq | A simple sequence generater |
| mvgamma | Multivariate gamma function |
| MVStocks | Multivariate Variables for Stocks |
| Params.subsets | Organize the subsets of the parameters by taking away the... |
| parLinkFun | Transform the mean function in the GLM framework. |
| parMeanFun | Transform the mean function in the GLM framework. |
| parMeanFunGrad | The gradient for the mean function in the GLM framework. |
| par.transform | Description |
| par.transform2 | Transform the parameters from the original scale to the new... |
| P.matrix | Generate the P matrices for the moving knots model |
| pochhammer | Pochhammer symbol |
| predict_fformpp | Function to predict forecast error measures from the the... |
| progressbar | Very Simple progress bar for "for loops" |
| RandomWalkMetropolis | Random walk Metropolis algorithm. |
| rbeta2 | The reparameterized beta distribution |
| rdist | Euclidean distance matrix between two matrices |
| rhex | Random hex |
| rlnorm2 | Log-normal distribution with alternative parametrization. |
| rmixnorm | Generate random variables from univariate and multivariate... |
| rmixnorm.ts | AR-type random variables from mixture of normals |
| save.all | Save all the objects to a folder. |
| set.crossvalid | Setup cross-validation |
| SGLD | Stochastic MCMC using Stochastic gradient Langevin dynamics |
| Sigma4betaFun | Calculate the variance for the prior of coefficients (beta)... |
| size | Print object.size |
| StdData | StdData |
| stock2covariates | Construct time series covariates. |
| tr | trace of a matrix |
| transform_features | Function to transform features |
| vech | calculating a vector |
| vech2m | Convert from the vech vector to the full matrix. |
| whichInd | Raw indices finder for array. |
| Xmats.x.delta.xi | Preform X_i multiply Dev xi |
| X.x.delta.xi | Preform X multiply Dev xi |
