A0N_MLEdensity_WOE__jointQ_Bootstrap
                        Compute the maximum likelihood function (joint
                        Q models) - Bootstrap version
A0N_MLEdensity_WOE__jointQ_sepSigma_Bootstrap
                        Compute the maximum likelihood function ("joint
                        Q" models for separate Sigma estimation) -
                        Bootstrap version
A0N_MLEdensity_WOE__sepQ_Bootstrap
                        Compute the maximum likelihood function ("sep
                        Q" models) - Bootstrap version
A0N__computeBnAn_jointQ
                        Compute the cross-section loadings of yields of
                        a canonical A0_N model ("joint Q" models)
A0N__computeBnAn_sepQ   Compute the cross-section loadings of yields of
                        a canonical A0_N model ("sep Q" models)
BR_jps_out              Replications of the JPS (2014) outputs by Bauer
                        and Rudebusch (2017)
BUnspannedAdapJoint     Transform B_spanned into B_unspanned for jointQ
                        models
BUnspannedAdapSep       Transform B_spanned into B_unspanned for sepQ
                        models
BUnspannedAdapSep_BS    Obtain the full form of B unspanned for "sep Q"
                        models within the bootstrap setting
Bootstrap               Generates the bootstrap-related outputs
BootstrapBoundsSet      Builds the confidence bounds and graphs
                        (Bootstrap set)
DataForEstimation       Retrieve data from Excel and build the database
                        used in the model estimation
DataSet_BS              Prepare the factor set for GVAR models
                        (Bootstrap version)
DatabasePrep            Prepare the GVARFactors database
FEVDandGFEVDbs_jointQ   Creates the confidence bounds and the graphs of
                        FEVDs and GFEVDs after bootstrap ("joint Q"
                        models)
FEVDandGFEVDbs_jointQ_Ortho
                        Creates the confidence bounds and the graphs of
                        FEVDs and GFEVDs after bootstrap (JLL-based
                        models)
FEVDandGFEVDbs_sepQ     Creates the confidence bounds and the graphs of
                        FEVDs and GFEVDs after bootstrap ("sep Q"
                        models)
FEVDgraphsJLLOrtho      FEVDs graphs for orthogonalized risk factors of
                        JLL-based models
FEVDgraphsJoint         FEVDs graphs for ("joint Q" models)
FEVDgraphsSep           FEVDs graphs for ("sep Q" models)
FEVDjoint               FEVDs for "joint Q" models
FEVDjointOrthogoJLL     Orthogonalized FEVDs for JLL models
FEVDjointOrthogoJLL_BS
                        FEVDs after bootstrap for JLL-based models
FEVDjoint_BS            FEVDs after bootstrap for "joint Q" models
FEVDsep                 FEVDs for "sep Q" models
FEVDsep_BS              FEVDs after bootstrap for "sep Q" models
FMN__Rotate             Performs state rotations
FactorsGVAR             Data: Risk Factors for the GVAR - Candelon and
                        Moura (2021)
FitgraphsJoint          Model fit graphs for ("joint Q" models)
FitgraphsSep            Model fit graphs for ("sep Q" models)
ForecastYields          Gather bond yields forecasts for all the model
                        types
ForecastYieldsJointQ    Bond yields forecasts ("joint Q" models)
ForecastYieldsSepQ      Bond yields forecasts ("sep Q" models)
Functionf               Set up the vector-valued objective function
                        (Point estimate)
Functionf_Boot          Set up the vector-valued objective function
                        (Bootstrap)
GFEVDgraphsJLLOrtho     GFEVDs graphs for orthogonalized risk factors
                        of JLL-based models
GFEVDgraphsJoint        GFEVDs graphs for ("joint Q" models)
GFEVDgraphsSep          GFEVDs graphs for ("sep Q" models)
GFEVDjoint              GFEVDs for "joint Q" models
GFEVDjointOrthoJLL      Orthogonalized GFEVDs for JLL models
GFEVDjointOrthoJLL_BS   GFEVDs after bootstrap for JLL-based models
GFEVDjoint_BS           GFEVDs after bootstrap for "joint Q" models
GFEVDsep                GFEVDs for "sep Q" models
GFEVDsep_BS             GFEVDs after bootstrap for "sep Q" models
GIRFSep                 GIRFs for "sep Q" models
GIRFSep_BS              GIRFs after bootstrap for "sep Q" models
GIRFgraphsJLLOrtho      GIRFs graphs for orthogonalized risk factors of
                        JLL-based models
GIRFgraphsJoint         GIRFs graphs for ("joint Q" models)
GIRFgraphsSep           GIRFs graphs for ("sep Q" models)
GIRFjoint               GIRFs for "joint Q" models
GIRFjointOrthoJLL       Orthogonalized GIRFs for JLL models
GIRFjointOrthoJLL_BS    GIRFs after bootstrap for JLL-based models
GIRFjoint_BS            GIRFs after bootstrap for "joint Q" models
GVAR                    Estimate a GVAR(1) and a VARX(1,1,1)
GaussianDensity         computes the density function of a gaussian
                        process
GraphicalOutputs        Generate the graphical outputs for the selected
                        models (Point estimate)
IRFandGIRFbs_jointQ     Creates the confidence bounds and the graphs of
                        IRFs and GIRFs after bootstrap ("joint Q"
                        models)
IRFandGIRFbs_jointQ_Ortho
                        Creates the confidence bounds and the graphs of
                        IRFs and GIRFs after bootstrap (JLL-based
                        models)
IRFandGIRFbs_sepQ       Creates the confidence bounds and the graphs of
                        IRFs and GIRFs after bootstrap ("sep Q" models)
IRFgraphsJLLOrtho       IRFs graphs for orthogonalized risk factors of
                        JLL-based models
IRFgraphsJoint          IRFs graphs for ("joint Q" models)
IRFgraphsSep            IRFs graphs for ("sep Q" models)
IRFjoint                IRFs for "joint Q" models
IRFjointOrthoJLL        Orthogonalized IRFs for JLL models
IRFjointOrthoJLL_BS     IRFs after bootstrap for JLL-based models
IRFjoint_BS             IRFs after bootstrap for "joint Q" models
IRFsep                  IRFs for "sep Q" models
IRFsep_BS               IRFs after bootstrap for "sep Q" models
IdxAllSpanned           Find the indexes of the spanned factors
IdxSpanned              Extract the indexes related to the spanned
                        factors in the variance-covariance matrix
InputsForMLEdensity     Generates several inputs that are necessary to
                        build the likelihood function
InputsForMLEdensity_BS
                        Generates several inputs that are necessary to
                        build the likelihood function - Bootstrap
                        version
InputsForOutputs        Collect the inputs that are used to construct
                        the numerical and the graphical outputs
JLL                     Set of inputs present at JLL's P-dynamics
K1XQStationary          Impose stationarity under the Q-measure
LabFac                  Generates the labels factors
LabelsSpanned           Generate the labels of the spanned factors
LabelsStar              Generate the labels of the star variables
MLEdensity_jointQ       Compute the maximum likelihood function ("joint
                        Q" models)
MLEdensity_jointQ_sepSigma
                        Compute the maximum likelihood function ("joint
                        Q" models for separate Sigma estimation)
MLEdensity_sepQ         Compute the maximum likelihood function ("sep
                        Q" models)
Maturities              Create a vector of numerical maturities in
                        years
ModelPara               Replications of the JPS (2014) outputs by the
                        MultiATSM package
MultiATSM               ATSM Package
NumOutputs              Construct the model numerical outputs (model
                        fit, IRFs, GIRFs, FEVDs, and GFEVDs)
NumOutputs_Bootstrap    Numerical outputs (IRFs, GIRFs, FEVD, and
                        GFEVD) for bootstrap
Optimization            Peform the minimization of mean(f)
Optimization_Boot       Peform the minimization of mean(f) (adapted for
                        the bootstrap setting)
OutputConstructionJoint
                        Numerical outputs (variance explained, model
                        fit, IRFs, GIRFs, FEVDs, and GFEVDs) for "joint
                        Q" models
OutputConstructionJoint_BS
                        Gathers all the model numerical ouputs after
                        bootstrap for "joint Q" models
OutputConstructionSep   Numerical outputs (variance explained, model
                        fit, IRFs, GIRFs, FEVDs, and GFEVDs) for "sep
                        Q" models
OutputConstructionSep_BS
                        Gathers all the model numerical ouputs after
                        bootstrap for "sep Q" models
ParaLabels              Create the variable labels used in the
                        estimation
PdynamicsSet_BS         Compute some key parameters from the P-dynamics
                        (Bootstrap set)
RMSEjoint               Compute the root mean square error ("joint Q"
                        models)
RMSEsep                 Compute the root mean square error ("sep Q"
                        models)
Reg_K1Q                 Estimate the risk-neutral feedbak matrix K1Q
                        using linear regressions
Reg__OLSconstrained     Restricted OLS regression
RemoveNA                Exclude series that contain NAs
RiskFactors             Data: Risk Factors - Candelon and Moura (2021)
RiskFactorsGraphs       Spanned and unspanned factors plot
RiskFactorsPrep         Builds the complete set of time series of the
                        risk factors (spanned and unspanned)
SpannedFactorsSepQ      Gather all spanned factors ("sep Q" models)
SpannedFactorsjointQ    Gather all spanned factors ("joint Q" models)
Spanned_Factors         Compute the country-specific spanned factors
StarFactors             Generates the star variables necessary for the
                        GVAR estimation
TradeFlows              Data: Trade Flows - Candelon and Moura (2021)
Transition_Matrix       Compute the transition matrix required in the
                        estimation of the GVAR model
VAR                     Estimates a VAR(1)
VarianceExplainedJoint
                        Percentage explained by the spanned factors of
                        the variations in the set of observed yields
                        for "joint Q" models
VarianceExplainedSep    Percentage explained by the spanned factors of
                        the variations in the set of observed yields
                        for "sep Q" models
Yields                  Data: Yields - Candelon and Moura (2021)
YieldsFitJoint          Computes two measures of model fit for bond
                        yields
YieldsFitsep            Computes two measures of model fit for bond
                        yields
aux2true                Map auxiliary (unconstrained) parameters a to
                        constrained parameters b
bound2x                 Transform a number bounded between a lower
                        bound and upper bound to x by:
contain                 Check whether one element is a subset of
                        another element
df__dx                  Computes numerical first order derivative of
                        f(x)
f_with_vectorized_parameters
                        Use function f to generate the outputs from a
                        ATSM
getpara                 Extract the parameter values from varargin
getx                    Obtain the auxiliary values corresponding to
                        each parameter, its size and its name
killa                   Eliminates the @
pca_weights_one_country
                        Weigth matrix from principal components (matrix
                        of eigenvectors)
pos2x                   Transform a positive number y to back to x by:
sqrtm_robust            Compute the square root of a matrix
true2aux                Map constrained parameters b to unconstrained
                        auxiliary parameters a.
update_para             converts the vectorized auxiliary parameter
                        vector x to the parameters that go directly
                        into the likelihood function.
x2bound                 Transform x to a number bounded btw lb and ub
                        by:
x2pos                   Transform x to a positive number by: y =
                        log(e^x + 1)
