Visual Studio Magazine

Neural Network Time Series Regression Using Python

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 ...
Investopedia

Master ARIMA: Your Guide to Time Series Forecasting

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 ...
InfoWorld

An introduction to time series forecasting

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 ...
JSTOR Daily

A Robust Regression Model for a First-Order Autoregressive Time Series with Unequal Spacing: Application to Water Monitoring

This is a preview. Log in through your library . Abstract Time series arise often in environmental monitoring settings, which typically involve measuring processes repeatedly over time. In many such ...
JSTOR Daily

Testing Model Adequacy for Some Markov Regression Models for Time Series

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 ...
Investopedia

Stepwise Regression Explained: Uses, Benefits, and Drawbacks

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 ...