Table 5 Price modelling by FVAR-FTN.

From: Enhanced forecasting of rice price and production in Malaysia using novel multivariate fuzzy time series models

Mean dependent var

899.6203

S.D. dependent var

228.2951

Sum square resid

1,355,573

S.E. of regression

242.7714

R-square

0.446610

Adjusted R-square

0.630841

F(24, 23)

0.073416

P-value(F)

0.031948

MAPE

0.204328

Durbin-Watson

1.984598

  1. F-tests of zero restrictions:
  2. \({\text{All lags of TPd F}}\left( {{\text{12}},{\text{ 23}}} \right)\,=\,0.{\text{9964 }}\left[ {0.0{\text{481}}} \right].\)\({\text{All lags of TPr F}}\left( {{\text{12}},{\text{ 23}}} \right)\,=\,0.{\text{79335 }}\left[ {0.0{\text{653}}} \right].\)\({\text{All vars, lag 12 F}}\left( {{\text{2, 23}}} \right)\,{\text{ = }}\,{\text{2}}{\text{.0885 }}\left[ {{\text{0}}{\text{.0146}}} \right].\).
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