%% Specify Response Names and Include Linear Time Trend
% Consider adding a linear time trend term to the 3-D VAR(4) model of mw_a042a8bf-0786-4ee7-94fa-c9d4ce1ea04f:
% \left[ {\begin{array}{*{20}{l}}
% {\texttt{INFL}_t}\\
% {\texttt{UNRATE}_t}\\
% {\texttt{FEDFUNDS}_t}
% \end{array}} \right] = c + \delta t +\sum\limits_{j = 1}^4 {{\Phi _j}\left[ {\begin{array}{*{20}{l}}
% {\texttt{INFL}_{t-j}\\
% {\texttt{UNRATE}_{t-j}\\
% {\texttt{FEDFUNDS}_{t-j}
% \end{array}} \right]} + \left[ {\begin{array}{*{20}{c}}
% {{\varepsilon _{1,t}}}\\
% {{\varepsilon _{2,t}}}\\
% {{\varepsilon _{3,t}}}
% \end{array}} \right].
% Create a diffuse prior model for the 3-D VAR(4) model parameters. Specify response variable names.

numseries = 3;
numlags = 4;
seriesnames = ["INFL"; "UNRATE"; "FEDFUNDS"];
PriorMdl = diffusebvarm(numseries,numlags,'SeriesNames',seriesnames,...
    'IncludeTrend',true)

% Copyright 2020 The MathWorks, Inc.
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