One of the most common issues I encounter in data cleaning and exploratory analysis is handling missing data. First, we need to understand that there is no perfect method to solve this problem. Different issues have different data imputation methods—time series analysis, machine learning, regression models, etc., making it difficult to provide a universal solution. … Read more
Using text from 200 million pages of 13,000 local US newspapers and machine learning methods, we constructed a measure of economic sentiment at national and state levels that spans 170 years, extending existing indicators in both time series and cross-section. Even after controlling for common predictive factors and monetary policy decisions, our measure can still … Read more
This article is about 11,000 words long and is recommended to be read in over 10 minutes. This is a survey overview of large models for time series and spatio-temporal data. Time-related data, especially time series and spatio-temporal data, are ubiquitous in real-world applications. These data capture measurements of dynamic systems and are generated in … Read more