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Population-Wide Depression Incidence Forecasting Comparing Autoregressive Integrated Moving Average and Vector Autoregressive Integrated Moving Average to Temporal Fusion Transformers: Longitudinal Observational Study

Population-Wide Depression Incidence Forecasting Comparing Autoregressive Integrated Moving Average and Vector Autoregressive Integrated Moving Average to Temporal Fusion Transformers: Longitudinal Observational Study

Combining the Kwiatkowski-Phillips-Schmidt-Shin tests and augmented Dickey-Fuller test, we determined that both depression and unemployment were integrated of order 1 and first-order differencing applied to both variables. We then tested for significant autocorrelation in the first to third data lags. To avoid overfitting, the combination of the orders of the autoregressive and moving average components were set in the range from 0 to 3 and from 0 to 2, respectively.

Deliang Yang, Yiyi Tang, Vivien Kin Yi Chan, Qiwen Fang, Sandra Sau Man Chan, Hao Luo, Ian Chi Kei Wong, Huang-Tz Ou, Esther Wai Yin Chan, David Makram Bishai, Yingyao Chen, Martin Knapp, Mark Jit, Dawn Craig, Xue Li

J Med Internet Res 2025;27:e67156