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Table 2 Fitting criteria of the ZIP and ZINB models with the training dataset

From: Using a zero-inflated model to assess gene flow risk and coexistence of Brassica napus L. and Brassica rapa L. on a field scale in Taiwan

Dispersal kernel function

ZIP model

ZINB model

RMSE

Adj. R2

AIC

BIC

RMSE

Adj. R2

AIC

BIC

Log-sech

0.01048

0.00286

− 16,963

− 16,954

0.00823

0.38911

− 17,859

− 17,852

Exponential power

0.01049

− 0.001

− 16,956

− 16,947

0.00823

0.38925

− 17,859

− 17,852

Power law

0.01044

0.01014

− 16,976

− 16,967

0.00826

0.38495

− 17,846

− 17,839

Logistic

0.01043

0.01097

− 16,978

− 16,969

0.00826

0.38517

− 17,847

− 17,840

2Dt

0.01043

0.01097

− 16,978

− 16,969

0.00824

0.38769

− 17,855

− 17,847

Gamma

0.01,064

− 0.0292

− 16904

− 16,895

0.00823

0.38884

− 17,858

− 17,851

WALD

0.01044

0.00994

− 16,976

− 16,967

0.00825

0.38542

− 17,848

− 17,841

Weibull

0.01043

0.01064

− 16,977

− 16,968

0.00823

0.38947

− 17,860

− 17,853

Neg. Exponential

0.01044

0.00989

− 16,977

− 16,966

0.00828

0.38183

− 17,838

− 17,829

Log-normal

0.01,044

0.00954

− 16,975

− 16,966

0.00824

0.38717

− 17,853

− 17,846

Gaussian

0.01044

0.00971

− 16,977

− 16,965

0.00826

0.38444

− 17,846

− 17,837

  1. RMSE: root mean square error; adj. R2: adjusted coefficient of determination; AIC: Akaike’s information criterion; BIC: Schwarz’s Bayesian information criterion; MSPR: mean squared prediction error