Results show that, under thestated assumptions, estimates from the new method based on full decompositionof a series is the best (in terms of the accuracy measures) when compared withother two new and the existing methods.doi:10.4236/ojs.2018.82025I. S. IwuezeE. C. NwoguV. U. Nlebedim...
The comparison and classification of time series is an important issue in practical time series analysis. For these purposes, various methods have been proposed in the literature, but all have shortcomings, especially when the observed time series have different sample sizes. In this paper, we prop...
Measuring the impact of sales promotions: A comparison of three time-series methods The first approach is based on Holt-Winter's method with an iterative technique to estimate a baseline. The second approach extends Winter's exponential smoothing by taking marketing events into account. The third ...
In this paper we presented some of the classical methods for the decomposition of a time series. We used moving average/median methods for removing trend and combined them with averaging and recursive methods for removing a seasonal component. We applied these methods to medical data of colorectal...
representation of each year of a time series. 关键词: phase-plane plots and then compared by looking at the insight that both methods offer particularly with respect to the seasonal be-havior of a variable. 关键词:从。。。的角度 Also, the possible combination of both approaches is explored,...
METHODS FOR THE CYCLICAL PATTERN DETERMINATION OF TIME-SERIES DATA USING A CLUSTERING APPROACH Cycles and other patterns within time-series data are determined. Time-series data are transformed into discretized sets of clustered data that are organized by time period. Comparison is made of the organi...
The Interrupted Time Series (ITS) is a quasi-experimental design commonly used in public health to evaluate the impact of interventions or exposures. Multiple statistical methods are available to analyse data from ITS studies, but no empirical investigat
Time-series processing is a major challenge in machine learning with enormous progress in the last years in tasks such as speech recognition and chaotic series prediction. A promising avenue for sequential data analysis is quantum machine learning, with
A comparison of methods for smoothing and gap filling time series of remote sensing observations - application to MODIS 10 LAI products, Biogeosciences, 10... S Kandasamy,F Baret,A Verger,... - 《Biogeosciences》 被引量: 0发表: 2013年 A comparison of methods for smoothing and gap filling ...
Cross-Sectional vs. Time Series Analysis Cross-sectional analysis is one of the two overarching comparison methods for stock analysis. Cross-sectional analysis looks at data collected at a single point in time, rather than over a period of time. The analysis begins with the establishment of resea...