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 ...
JSTOR Daily

Least Absolute Deviation Estimation for Fractionally Integrated Autoregressive Moving Average Time Series Models with Conditional Heteroscedasticity

We consider a unified least absolute deviation estimator for stationary and nonstationary fractionally integrated autoregressive moving average models with conditional heteroscedasticity. Its ...
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 ...
inc42

What Are Autoregressive Models? Here’s All You Need to Know

Autoregressive models are a statistical technique used to predict future values in a sequence based on its past values. It is essentially a fancy way of saying that it uses the past to predict the ...
ascopubs.org

Forecasting incidence and mortality rates of prostate cancer in older adults using autoregressive integrated moving average (ARIMA).

Prevalence of obesity/overweight and its relationship with incidence of pancreatic cancer in the US states using BRFSS and CDC WONDER database of 2021.
ascopubs.org

Forecasting incidence and mortality rates of bladder cancer in older adults using autoregressive integrated moving average (ARIMA).

Impact of trimodal therapy on survival outcomes in non-urothelial muscle-invasive bladder cancer: A nationwide analysis.