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Researchers develop model to accurately predict vessel turnaround time at ports

In the 21st century, as global trade expands and cargo volumes surge, ports face mounting pressure to operate efficiently. A ...
InfoWorld

3 forecasts about time-series forecasting

Pre-trained foundation models are making time-series forecasting more accessible and available, unlocking its benefits for smaller organizations with limited resources. Over the last year, we’ve seen ...
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 ...
ascopubs.org

Time Series Prediction of Lung Cancer Death Rates on the Basis of SEER Data

Synthetic Data Generation by Artificial Intelligence to Accelerate Research and Precision Medicine in Hematology Three models for yearly time series predictions were built: autoregressive integrated ...
JSTOR Daily

Hybrid quantile regression estimation for time series models with conditional heteroscedasticity

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 ...
JSTOR Daily

A CONSISTENT NONPARAMETRIC TEST ON SEMIPARAMETRIC SMOOTH COEFFICIENT MODELS WITH INTEGRATED TIME SERIES

In this paper, we propose a simple nonparametric test for testing the null hypothesis of constant coefficients against nonparametric smooth coefficients in a semiparametric varying coefficient model ...
ascopubs.org

Time Series Prediction of Lung Cancer Death Rates on the Basis of SEER Data

This study used SEER data from 1975 to 2018 and included 545,486 patients with lung cancer. The best parameters for ARIMA are ARIMA (p, d, q) = (0, 2, 2). In addition, the best parameter for SES was α ...