Table 7 Production modelling by FVAR-FTNest.

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

Mean dependent var

4.373613

S.D. dependent var

3.234498

Sum square resid

300.7512

S.E. of regression

3.616094

R-square

0.688360

Adjusted R-square

0.69872

F(24, 23)

0.008493

P-value(F)

0.002997

MAPE

0.183133

Durbin-Watson

1.768545

  1. F-tests of zero restrictions:
  2. \({\text{All lags of TPd}}\_{\text{est F}}\left( {{\text{12}},{\text{ 23}}} \right)\,=\,0.{\text{689}}0{\text{6 }}\left[ {0.0{\text{453}}} \right].\)\({\text{All lags of TPr}}\_{\text{est F}}\left( {{\text{12}},{\text{ 23}}} \right)\,=\,0.{\text{4}}0{\text{857 }}\left[ {0.0{\text{451}}} \right].\)\({\text{All vars, lag 12 F}}\left( {{\text{2, 23}}} \right)\,{\text{ = }}\,{\text{1}}{\text{.2519 }}\left[ {{\text{0}}{\text{.0417}}} \right].\).
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