The asymptotic distribution of residual autocorrelations and a score statistic are derived for checking model adequacy for some Markov regression models for time series. These models are natural ...

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 80, No. 5 (2018), pp. 975-993 (19 pages) Estimating conditional quantiles of financial time series is essential for ...

Why it's not a time series model: Decision trees are non-parametric models that partition the data into subsets based on a ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

The goal of a time series regression problem is best explained by a concrete example. Suppose you own an airline company and you want to predict the number of passengers you'll have next month based ...

Time series forecasts are used to predict a future value or a classification at a particular point in time. Here’s a brief overview of their common uses and how they are developed. Industries from ...

Machines fail. By creating a time-series prediction model from historical sensor data, you can know when that failure is coming Anomaly detection covers a large number of data analytics use cases.