시그모이드 함수를 이용한 파리 종에 대한 성장곡선모형의 비교
A Comparison of Growth Curve Models for Forensically Important Flies Using Sigmoid Functions
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To estimate postmortem interval, it is essential to obtain information regarding fly growth. Analyzing the relationship between growth period and body length using a sigmoid function is widely accepted in animal science. However, in forensic entomology, it is difficult to find studies related to growth period and body length. Therefore, we compared growth curve models for forensically important flies using sigmoid functions. we used the data from flour fly species ( Calliphora lata, Calliphora vicina, Chrysomya pinguis , and Lucilia illustris ) and fited these against five sigmoid functions: quadratic-plateau model, logistic model, Gompertz model, von Bertalanffy model, and Brody model. Model evaluation criteria were, R 2 mean squared error (MSE), Akaike information criterion (AIC), and Bayesian information criterion (BIC). The von Bertalanffy model yielded the highest R 2 value and the lowest MSE, AIC, and BIC values for C. lata , whereas the logistic model was the best fit for the data from the other three species C. vicina, Ch. pinguis , and L. illustris.
Abstract
To estimate postmortem interval, it is essential to obtain information regarding fly growth. Analyzing the relationship between growth period and body length using a sigmoid function is widely accepted in animal science. However, in forensic entomology, it is difficult to find studies related to growth period and body length. Therefore, we compared growth curve models for forensically important flies using sigmoid functions. we used the data from flour fly species ( Calliphora lata, Calliphora vicina, Chrysomya pinguis , and Lucilia illustris ) and fited these against five sigmoid functions: quadratic-plateau model, logistic model, Gompertz model, von Bertalanffy model, and Brody model. Model evaluation criteria were, R 2 mean squared error (MSE), Akaike information criterion (AIC), and Bayesian information criterion (BIC). The von Bertalanffy model yielded the highest R 2 value and the lowest MSE, AIC, and BIC values for C. lata , whereas the logistic model was the best fit for the data from the other three species C. vicina, Ch. pinguis , and L. illustris.
참고문헌 (30)
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