The cumulative sum (CUSUM) control chart and the multivariate anomaly detection with the generative adversarial network (MAD-GAN) were compared for monitoring the time series data. However, it is not correct because the one-class classification was considered for the training phase and the...

This paper presents a comprehensive study of statistical and machine learning methods for predicting daily and weekly volatility of the following four cryptocurrencies: Bitcoin, Ethereum, Litecoin, and Monero. Several methods, i.e., HAR, ARFIMA, GARCH, LASSO, ridge regression, SVR, MLP, fuzzy...

In this paper, we estimate the distribution of future inflation and growth in real gross domestic product (GDP) for the Canadian economy at a daily frequency. To do this, we model the conditional moments (mean, variance, skewness and kurtosis) of inflation and GDP growth as moving averages of...

Sustainable Development Goal (SDG) 5 aims to “achieve gender equality and empower all women and girls,” and gender-specific aspects are embedded in several other SDGs. However, routine national data collection to produce gender data for SDG monitoring and other purposes is limited. Within...

I provide formulas for the influence function of two common misallocation statistics: TFP loss from misallocation and potential TFP gain from reallocation. I also show how to use a finite-difference approximation to Gateaux derivatives to obtain sample analogs to influence functions for...

To solve the problem of poor performance of deep neural network models due to insufficient data, a simple yet effective interpolation-based data augmentation method is proposed: MSMix (Manifold Swap Mixup). This method feeds two different samples to the same deep neural network model, and then...

For two periods an expert E announces his forecast of the state to a decision-maker D who chooses action. They disagree about the precision of the probability assessments. At the end of period 1 the state is observed. In the last period E makes announcements more extreme than his forecasts....