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Full-Text Articles in Physical Sciences and Mathematics
A Dynamic-Trend Exponential Smoothing Model, Don Miller, Dan Williams
A Dynamic-Trend Exponential Smoothing Model, Don Miller, Dan Williams
Publications and Research
Forecasters often encounter situations in which the local pattern of a time series is not expected to persist over the forecasting horizon. Since exponential smoothing models emphasize recent behavior, their forecasts may not be appropriate over longer horizons. In this paper, we develop a new model in which the local trend line projected by exponential smoothing converges asymptotically to an assumed future long-run trend line, which might be an extension of a historical long-run trend line. The rapidity of convergence is governed by a parameter. A familiar example is an economic series exhibiting persistent long-run trend with cyclic variation. This …
Strokes Of Existence: The Connection Of All Things, Mari Gorman
Strokes Of Existence: The Connection Of All Things, Mari Gorman
Graduate Student Publications and Research
Acted or real—and all life is real whether one is acting or not—the common denominator and consistent, ubiquitous reality of life and all behavior is that it manifests in the form of relationships on all scales. But what is a relationship? Until now, the answer to this question has not been sufficiently known. As a result of many years of empirical research that began with the aim of discovering what is going on in a gifted actor when s/he is playing a character that can be observed and experienced as a living, intuitive being, and based on the knowledge that …
Hierarchical Linear Modeling In Organizational Research: Longitudinal Data Outside The Context Of Growth Modeling, Irvin Sam Schonfeld, David Rindskopf
Hierarchical Linear Modeling In Organizational Research: Longitudinal Data Outside The Context Of Growth Modeling, Irvin Sam Schonfeld, David Rindskopf
Publications and Research
Organizational researchers, including those carrying out occupational stress research, often conduct longitudinal studies. Hierarchical linear modeling (HLM; also known as multilevel modeling and random regression) can efficiently organize analyses of longitudinal data by including within- and between-person levels of analysis. A great deal of longitudinal research has been conducted in the context of growth studies in which change in the dependent variable is examined in relation to the passage of time. HLM can treat longitudinal data, including data outside the context of the growth study, as nested data, reducing the problem of censoring. Within-person equation coefficients can represent the impact …