In this paper, we provide theoretical justification for the application of higher degree fuzzy transform in time series analysis. Under the assumption that a time series can be additively decomposed into a trend-cycle, a seasonal component and a random noise, we demonstrate that the higher degree fuzzy transform technique can be used for the estimation of the trend-cycle, which is one of the ba...

Introduction Conclusions References Tables Figures Back Close Abstract Introduction Conclusions References Tables Figures Back Close Abstract A seasonal-trend decomposition technique based on a locally-weighted regression smoothing (Loess) approach has been used to decompose monthly ozone concentrations at Mace Head (Ireland) into trend, seasonal and irregular components. The trend component sh...

A seasonal-trend decomposition technique based on a locally-weighted regression smoothing (Loess) approach has been used to decompose monthly ozone concentrations at Mace Head (Ireland) into trend, seasonal and irregular components. The trend component shows a steady increase from 1990–2004, which is confirmed by statistical testing which shows that ozone concentrations at Mace Head have increa...

This paper suggests a new semi-parametric multivariate approach to seasonal adjustment. The primary innovation is to use a large dimensional factor model of cross section dependence to estimate the trend component in the seasonal decomposition of each time series. Because the trend component is speci…ed to capture covariation between the time series, common changes in the level of the time seri...

Seasonal variation in water quality of Anchar Lake was evaluated using multivariate statistical techniques- principal component analysis (PCA) and cluster analysis (CA). Water quality data collected during 4 seasons was analyzed for 13 parameters. ANOVA showed significant variation in pH (F3 = 10.86, P < 0.05), temperature (F3 = 65, P

Seasonal variation in water quality of Anchar Lake was evaluated using multivariate statistical techniques- principal component analysis (PCA) and cluster analysis (CA). Water quality data collected during 4 seasons was analyzed for 13 parameters. ANOVA showed significant variation in pH (F3 = 10.86, P < 0.05), temperature (F3 = 65, P

Seasons are the complex nonlinear response of the physical climate system to regular annual solar forcing. There is no a priori reason why they should remain fixed/invariant from year to year, as is often assumed in climate studies when extracting the seasonal component. The widely used econometric variant of Census Method II Seasonal Adjustment Program (X-11), which allows for year-to-year var...

Seasonally driven cycles of incidence have been consistently observed for a range of directly transmitted pathogens. Though frequently observed, the mechanism of seasonality for directly transmitted human pathogens is rarely well understood. Despite significant annual variation in magnitude, measles outbreaks in Niger consistently begin in the dry season and decline at the onset of the seasonal...

Eleven sequential size-based hydroacoustic surveys conducted with a 200 kHz split-beam transducer during the summers of 2011 and 2012 were used to quantify seasonal declines in fish abundance in a boreal reservoir in Manitoba, Canada. Fish densities were sufficiently low to enable single target resolution and tracking. Target strengths converted to log2-based size-classes indicated that smaller...

The series on average hours worked in the manufacturing sector is a key leading indicator of the U.S. business cycle. The paper deals with robust estimation of the cyclical component for the seasonally adjusted time series. This is achieved by an unobserved components model featuring an irregular component that is represented by a Gaussian mixture with two components. The mixture aims at captur...