Results 71 to 80 of about 105,549 (303)
Trends in Rheumatoid Arthritis Mortality Among Postmenopausal Women in the United States, 1999–2023
iMetaMed, EarlyView.RA‐related mortality among U.S. postmenopausal women has markedly declined since 1999. Despite this overall progress, significant inequalities by race, region, and age highlight ongoing challenges in achieving equitable health outcomes. ABSTRACT Rheumatoid arthritis (RA) disproportionately affects postmenopausal women, who are at an increased risk of ...
Yuhui Zhao +4 more
wiley +1 more source
Studying dynamic social processes with ARIMA modeling [PDF]
International Journal of Social Research Methodology, 2013 With the increasing use of information and communication technologies, there is a wealth of longitudinal data available, which open up new research directions. This availability necessitates special analytical tools, namely time series analysis methods.
Vasileiadou, E., Vliegenthart, R.
openaire +4 more sources
Forecasting Natural Gas Prices in Real Time
Journal of Applied Econometrics, EarlyView.ABSTRACT This paper provides a comprehensive analysis of the forecastability of the real price of natural gas in the United States at the monthly frequency considering a universe of models that differ in complexity and economic content. We find that considerable reductions in mean‐squared prediction error relative to a no‐change benchmark can be ...
Christiane Baumeister +3 more
wiley +1 more source
Time Series Forecasts of International Tourism Demand for Australia, [PDF]
This paper examines stationary and nonstationary time series by formally testing for the presence of unit roots and seasonal unit roots prior to estimation, model selection and forecasting.
Christine Lim, Michael McAleer
core
Time series analysis to forecast temperature change [PDF]
, 2010 ARIMA models are often used to model the evolution in time of economic issues. We demonstrate that an ARIMA model is also valuable in the environmental field, where the evolution of climate change is causing many concerns.
Van Hecke, Tanja
core +1 more source
Comparison of daily rainfall forecasting using multilayer perceptron neural network model [PDF]
, 2014 Rainfall is important in predicting weather forecast particularly to the agriculture sector and also in environment which gives great contribution towards the economy of the nation. Thus, it is important for the hydrologists to forecast daily rainfall in
Ismail, Shuhaida +3 more
core +3 more sources
Journal of Clinical Laboratory Analysis, EarlyView.This study applies machine learning methods, specifically Random Forest and Bagged CART, to classify Cryptosporidium spp. infections among children and identify key risk factors. The Bagged CART model demonstrated superior sensitivity and predictive performance, highlighting household crowding and water source as the most influential determinants of ...
Türkan Mutlu Yar +2 more
wiley +1 more source
Combining disaggregate forecasts for inflation: The SNB's ARIMA model: the SNB's ARIMA model
, 2013 ISSN:1661 ...
Huwiler, Marco, Kaufmann, Daniel
openaire +2 more sources
Quality and Reliability Engineering International, EarlyView.ABSTRACT In modern manufacturing environments, traditional statistical process control (SPC) methods often struggle with complex, dynamic data patterns, particularly when observations are autocorrelated. Control charts are useful tools used in SPC to detect any significant drift in a process.
Jeanette Maria Louw +3 more
wiley +1 more source
Crime Prediction Utilizing ARIMA Model
BCP Business & Management, 2023 With the development of society and the progress of human beings, the issue of crime has attracted more attention. This research uses one of the most common time series models named the ARIMA model as the main algorithm to predict the crime data by month in San Francisco from 2003 to 2015, obtained from Kaggle.
openaire +1 more source