Nature

Continuous-Time Autoregressive Moving Average Processes

Continuous-Time Autoregressive Moving Average (CARMA) processes extend the classical discrete-time ARMA framework to continuous time, offering a flexible modelling approach for phenomena where ...
JSTOR Daily

A Note on the Estimation of the Parameters of the Autoregressive-Moving Average Process

This is a preview. Log in through your library . Abstract Patterson & Thompson (1971) have described a modified maximum likelihood technique for estimating variance components in the additive mixed ...
JSTOR Daily

A Fast Algorithm for the Exact Likelihood of Stationary and Partially Nonstationary Vector Autoregressive-Moving Average Processes

This is a preview. Log in through your library . Abstract An expression for the likelihood function of a stationary vector autoregressive-moving average process is developed. The expression is very ...
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

Time series forecasting with ARMA and InfluxDB

Autoregressive moving average models have a number of advantages including simplicity. Here’s how to use an ARMA model with InfluxDB. An ARMA or autoregressive moving average model is a forecasting ...
Investopedia

Box-Jenkins Model Explained: Uses, Methodology, and Forecasting

Gordon Scott has been an active investor and technical analyst or 20+ years. He is a Chartered Market Technician (CMT). Gordon Scott has been an active investor and technical analyst or 20+ years. He ...
International Monetary Fund

Inflation in Tajikistan: Forecasting Analysis and Monetary Policy Challenges

Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author (s) and do not necessarily represent those ...