Longitudinal research using cross-lagged designs allows us to infer causal directionality (Kearney, 2017). However, a shortcoming of many prior behavioral studies that have used predictive models is that they have not controlled for children's initial skill levels (e.g., Blom & Boerma, 2019; ...
The dilated causal convolution network comprises 20 layers, each of which exponentially increases the dilation parameter: 2𝑖2i for the i-th layer. We employ an adaptive max-pooling layer as the last layer to squeeze the temporal dimension and output a vector of a fixed size. Here, represen...
A Bayesian bootstrapping and backtest density forecasts, which are based on a weighted threshold and quantile of a continuously ranked probability score, are developed. Developed backtesting procedures revealed that an estimated Seasonal autoregressive integrated moving average-generalized autoregressive score...
Woldu [9] used the ARDL model to study the bidirectional causal relationship between urban globalisation and CO2 emissions in Mozambique. With its rapid development, new-generation information technology such as big data analytics and machine learning can perform analysis and prediction by learning data...
A Bayesian bootstrapping and backtest density forecasts, which are based on a weighted threshold and quantile of a continuously ranked probability score, are developed. Developed backtesting procedures revealed that an estimated Seasonal autoregressive integrated moving average-generalized autoregressive score...