Assessment of autoregressive integrated moving average (ARIMA), generalized linear autoregressive moving average (GLARMA), and random forest (RF) time series regression models for predicting influenza A virus frequency in swine in Ontario, Canada.

Relative to the baseline summer season, the winter, spring, and fall season regression terms were all found to be highly significant ( P = 0.003, P = 0.0004, P = 0.001, respectively), indicating that season has a significant impact on the number of weekly diagnostic submissions.

also in 132,142 other papers

However, an increasing trend in the frequency of positive submissions based on monthly and weekly data was detected regardless of the modeling approach considered.

also in 63,971 other papers