GitHub

An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection

TSB-UAD is a new open, end-to-end benchmark suite to ease the evaluation of univariate time-series anomaly detection methods. Overall, TSB-UAD contains 12686 time series with labeled anomalies ...
archive

Continuous Univariate Distributions, Vol. 2 (Wiley Series in Probability and Statistics)

Can you chip in? As an independent nonprofit, the Internet Archive is fighting for universal access to quality information. We build and maintain all our own systems, but we don’t charge for access, ...
IEEE

Machine Learning for Univariate Time Series Imputation

Abstract: Missing data occur in almost real time series applications. Using incomplete data or ignoring missing values can cause inaccurate results and reduce system efficiency. Recovering missing ...
IEEE

LSTM Deep Learning vs ARIMA Algorithms for Univariate Time Series Forecasting: A case study

Abstract: This manuscript aims to study and compare the Long Short-Term Memory (LSTM) Deep learning to Auto regressive Integrated Moving Average (ARIMA) algorithms for a univariate time series, ...