log

PURPOSE

SYNOPSIS

DESCRIPTION

@info:
! @deftypefn {Function File} {@var{ts} =} log(@var{ts})
! @anchor{log}
! Apply the logarithm function to a Dynare time series object.
!
! @strong{Inputs}
! @table @var
! @item ts
! Dynare time series object, instantiated by @ref{dynSeries}
! @end table
!
! @strong{Outputs}
! @table @var
! @item ts
! Dynare time series object with transformed data field.
! @end table
!
! @strong{This function is called by:}
! None.
!
! @strong{This function calls:}
! None.
!
! @end deftypefn
@eod:

CROSS-REFERENCE INFORMATION

• log @info:

• log @info:
• AHessian function [AHess, DLIK, LIK] = AHessian(T,R,Q,H,P,Y,DT,DYss,DOm,DH,DP,start,mf,kalman_tol,riccati_tol)
• DsgeSmoother Estimation of the smoothed variables and innovations.
• DsgeVarLikelihood Evaluates the posterior kernel of the bvar-dsge model.
• PosteriorFilterSmootherAndForecast function PosteriorFilterSmootherAndForecast(Y,gend, type)
• bvar_density function bvar_density(maxnlags)
• bvar_toolbox function [ny, nx, posterior, prior, forecast_data] = bvar_toolbox(nlags)
• cmaes
• ig1fun Copyright (C) 2011 Dynare Team
• inverse_gamma_specification Computes the inverse Gamma hyperparameters from the prior mean and standard deviation.
• dsge_likelihood Evaluates the posterior kernel of a dsge model.
• dsge_posterior_kernel function [fval,cost_flag,ys,trend_coeff,info] = dsge_posterior_kernel(xparam1,gend,data,data_index,number_of_observations,no_more_missing_observations)
• dynare_estimation function dynare_estimation(var_list)
• dynare_estimation_1 function dynare_estimation_1(var_list_,dname)
• dynare_estimation_init function dynare_estimation_init(var_list_, gsa_flag)
• dynare_sensitivity Frontend to the Sensitivity Analysis Toolbox for DYNARE
• ep_residuals Inversion of the extended path simulation approach. This routine computes the innovations needed to
• evaluate_likelihood Evaluate the logged likelihood at parameters.
• evaluate_smoother Evaluate the smoother at parameters.
• gmhmaxlik function [PostMod,PostVar,Scale,PostMean] = ...
• log_trans_ Copyright (C) 2012 Dynare Team
• map_ident_ Copyright (C) 2012 Dynare Team
• read_data Written by Marco Ratto
• imcforecast Computes conditional forecasts.
• independent_metropolis_hastings_core PARALLEL CONTEXT
• kalman_filter Computes the likelihood of a stationnary state space model.
• kalman_filter_d Computes the diffuse likelihood of a state space model.
• kalman_filter_ss Computes the likelihood of a stationnary state space model (steady state kalman filter).
• missing_observations_kalman_filter Computes the likelihood of a state space model in the case with missing observations.
• missing_observations_kalman_filter_d Computes the diffuse likelihood of a state space model when some observations are missing.
• univariate_kalman_filter Computes the likelihood of a stationnary state space model (univariate approach).
• univariate_kalman_filter_d Computes the likelihood of a state space model (initialization with diffuse steps, univariate approach).
• univariate_kalman_filter_ss Computes the likelihood of a stationnary state space model (steady state univariate kalman filter).
• kernel_density_estimate Estimates a continuous density.
• lpdfgam Evaluates the logged GAMMA PDF at x.
• lpdfgbeta Evaluates the logged BETA PDF at x.
• lpdfig1 Evaluates the logged INVERSE-GAMMA-1 PDF at x.
• lpdfig2 Evaluates the logged INVERSE-GAMMA-2 PDF at x.
• lpdfnorm Evaluates the logged UNIVARIATE GAUSSIAN PDF at x.
• marginal_density function marginal = marginal_density()
• betapdf BETAPDF PDF of the Beta distribution
• exprnd Random samples from the exponential distribution with expectation a
• gampdf GAMPDF PDF of the Gamma distribution
• gamrnd This function produces independent random variates from the Gamma distribution.
• model_comparison Bayesian model comparison. This function computes Odds ratios and
• ms_mardd Applies to both linear and exclusion restrictions.
• ms_sbvar_setup function ms_sbvar_setup(options_)
• msstart2 function msstart2(options_)
• non_linear_dsge_likelihood Evaluates the posterior kernel of a dsge model using a non linear filter.
• auxiliary_particle_filter Evaluates the likelihood of a nonlinear model with a particle filter allowing eventually resampling.
• sequential_importance_particle_filter Evaluates the likelihood of a nonlinear model with a particle filter (optionally with resampling).
• plot_identification function plot_identification(params,idemoments,idehess,idemodel, idelre, advanced, tittxt, name, IdentifDirectoryName)
• prior_posterior_statistics_core PARALLEL CONTEXT
• priordens Computes a prior density for the structural parameters of DSGE models
• random_walk_metropolis_hastings_core PARALLEL CONTEXT
• simplex_optimization_routine Nelder-Mead like optimization routine.

SOURCE CODE

0001 function ts = log(ts)
0002 
0003 %@info:
0004 %! @deftypefn {Function File} {@var{ts} =} log(@var{ts})
0005 %! @anchor{log}
0006 %! Apply the logarithm function to a Dynare time series object.
0007 %!
0008 %! @strong{Inputs}
0009 %! @table @var
0010 %! @item ts
0011 %! Dynare time series object, instantiated by @ref{dynSeries}
0012 %! @end table
0013 %!
0014 %! @strong{Outputs}
0015 %! @table @var
0016 %! @item ts
0017 %! Dynare time series object with transformed data field.
0018 %! @end table
0019 %!
0020 %! @strong{This function is called by:}
0021 %! None.
0022 %!
0023 %! @strong{This function calls:}
0024 %! None.
0025 %!
0026 %! @end deftypefn
0027 %@eod:
0028 
0029 % Copyright (C) 2011 Dynare Team
0030 %
0031 % This file is part of Dynare.
0032 %
0033 % Dynare is free software: you can redistribute it and/or modify
0034 % it under the terms of the GNU General Public License as published by
0035 % the Free Software Foundation, either version 3 of the License, or
0036 % (at your option) any later version.
0037 %
0038 % Dynare is distributed in the hope that it will be useful,
0039 % but WITHOUT ANY WARRANTY; without even the implied warranty of
0040 % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
0041 % GNU General Public License for more details.
0042 %
0043 % You should have received a copy of the GNU General Public License
0044 % along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
0045 
0046 % AUTHOR(S) stephane DOT adjemian AT univ DASH lemans DOT fr
0047 
0048 if ~isa(ts,'dynSeries')
0049     error('dynSeries::log: Input argument has to be a Dynare time series object!')
0050 end
0051 
0052 if any(ts.data<eps)
0053     error('dynSeries::log: Input argument has to be strictly positive!')
0054 end
0055 
0056 ts.data = log(ts.data);