scholarly journals Time Trends and Persistence in the Snowpack Percentages by Watershed in Colorado

2021 ◽  
Author(s):  
Luis Alberiko Gil-Alana
Keyword(s):  
Long Memory ◽  
Time Trends ◽  
Time Trend ◽  
Significant Decline ◽  
Long Range Dependence ◽  
Annual Data ◽  
Long Memory Processes ◽  
Negative Time ◽  
Memory Pattern ◽  
Over Time

In this paper we investigate the time trend coefficients in snowpack percentages by watershed in Colorado, US, allowing for the possibility of long range dependence or long memory processes. Nine series corresponding to the following watersheds are examined: Arkansas, Colorado, Gunnison, North Platte, Rio Grande, South Platte, San Juan-Animas-Dolores-San Miguel, Yampa & White and Colorado Statewide, based on annual data over the last eighty years. The longest series start in 1937 and all end in 2019. The results indicate that most of the series display a significant decline over time, showing negative time trend coefficients, and thus supporting the hypothesis of climate change and global warming. Nevertheless, there is no evidence of a long memory pattern in the data.

scholarly journals Long Memory and Time Trends in Particulate Matter Pollution (PM2.5 and PM10) in the 50 U.S. States

2020 ◽  
Vol 59 (8) ◽  
pp. 1351-1367 ◽  
Author(s):  
Luis A. Gil-Alana ◽  
OlaOluwa S. Yaya ◽  
Oladapo G. Awolaja ◽  
Lorenzo Cristofaro
Keyword(s):  
Time Series ◽  
Particulate Matter ◽  
Air Quality ◽  
Long Memory ◽  
Time Trends ◽  
Quantitative Evidence ◽  
Quality Regulation ◽  
Pm2.5 And Pm10 ◽  
Negative Time ◽  
Daily Time

AbstractThis paper focuses on the analysis of the time series behavior of the air quality in the 50 U.S. states by looking at the statistical properties of particulate matter (PM10 and PM2.5) datasets. We use long daily time series of outdoor air quality indices to examine issues such as the degree of persistence as well as the existence of time trends in data. For this purpose, we use a long-memory fractionally integrated framework. The results show significant negative time trend coefficients in a number of states and evidence of long memory in the majority of the cases. In general, we observe heterogeneous results across counties though we notice higher degrees of persistence in the states on the west with respect to those on the east, where there is a general decreasing trend. It is hoped that the findings in the paper will continue to assist in quantitative evidence-based air quality regulation and policies.

scholarly journals Estimation of the self-similarity parameter in long memory processes

1970 ◽  
Vol 38 ◽  
pp. 32-37 ◽  
Author(s):  
MMA Sarker
Keyword(s):  
Long Memory ◽  
The Self ◽  
Similar Process ◽  
Long Range Dependence ◽  
Self Similarity ◽  
Similarity Parameter ◽  
Data Set ◽  
Memory Processes ◽  
Long Memory Processes ◽  
Self Similar

Long memory processes, where positive correlations between observations far apart in time and space decay very slowly to zero with increasing time lag, occur quite frequently in fields such as hydrology and economics. Stochastic processes that are invariant in distribution under judicious scaling of time and space, called self-similar process, can parsimoniously model the long-run properties of phenomena exhibiting long-range dependence. Four of the heuristic estimation approaches have been presented in this study so that the self-similarity parameter, H that gives the correlation structure in long memory processes, can be effectively estimated. Finally, the methods presented in this paper were applied to two observed time series, namely Nile River Data set and the VBR (Variable- Bit-Rate) data set. The estimated values of H for two data sets found from different methods suggest that all methods are not equally good for estimation. Keywords: Long memory process, long-range dependence, Self-similar process, Hurst Parameter, Gaussian noise. DOI: 10.3329/jme.v38i0.898 Journal of Mechanical Engineering Vol.38 Dec. 2007 pp.32-37  

scholarly journals Time trends of socioeconomic inequalities in adolescent smoking in Okinawa, Japan, 2008–2016: a repeated cross-sectional study

2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Minoru Takakura ◽  
Masaya Miyagi ◽  
Akira Kyan
Keyword(s):  
Time Trends ◽  
Parental Education ◽  
Cross Sectional Study ◽  
Socioeconomic Inequalities ◽  
School Type ◽  
Sectional Study ◽  
Cross Sectional ◽  
Japanese Adolescents ◽  
Index Of Inequality ◽  
Over Time

Abstract Background Smoking among Japanese adolescents has decreased noticeably. However, little is known whether the decreasing trend in adolescent smoking can be seen across all socioeconomic status (SES) groups. This study aimed to examine trends in socioeconomic inequalities in smoking among Japanese adolescents between 2008 and 2016. Methods We conducted a repeated cross-sectional study using data from three surveys of high school students in Okinawa, Japan, in 2008, 2012, and 2016. The study participants consisted of 7902 students in grades 10 through 12 (15–18 years). Smoking was assessed as current cigarette use. SES indicators included familial SES (parental education and family structure) and student’s own SES (school type). To evaluate absolute and relative inequalities, prevalence differences (PDs) and ratios (PRs) between low and high SES groups were estimated. The slope index of inequality (SII) and relative index of inequality (RII) were also calculated. Results Smoking prevalence among boys and girls significantly declined from 11.5% and 6.2% in 2008 to 4.7% and 1.9% in 2016, respectively. Similar decreasing trends in smoking were found among most of the SES groups. The PDs and SII for parental education in boys and family structure in girls decreased over time while those for school type persisted among boys and girls. The PRs and RII for school type in boys increased while those for other SES indicators among both sexes remained stable over time. Conclusions Smoking among Japanese adolescents has been declining and time trends of socioeconomic inequalities in smoking varied by absolute and relative measures. Further policies and/or interventions to reduce smoking inequalities should focus on the context of schools, especially in vocational high schools.

scholarly journals A harmonically weighted filter for cyclical long memory processes

2021 ◽  
Author(s):  
Federico Maddanu
Keyword(s):  
Spectral Density ◽  
Long Memory ◽  
Convergence In Probability ◽  
Simulation Methods ◽  
Integrated Process ◽  
Paleoclimatic Data ◽  
Memory Time ◽  
Long Memory Processes ◽  
Short Memory ◽  
Memory Parameter

AbstractThe estimation of the long memory parameter d is a widely discussed issue in the literature. The harmonically weighted (HW) process was recently introduced for long memory time series with an unbounded spectral density at the origin. In contrast to the most famous fractionally integrated process, the HW approach does not require the estimation of the d parameter, but it may be just as able to capture long memory as the fractionally integrated model, if the sample size is not too large. Our contribution is a generalization of the HW model, denominated the Generalized harmonically weighted (GHW) process, which allows for an unbounded spectral density at $$k \ge 1$$ k ≥ 1 frequencies away from the origin. The convergence in probability of the Whittle estimator is provided for the GHW process, along with a discussion on simulation methods. Fit and forecast performances are evaluated via an empirical application on paleoclimatic data. Our main conclusion is that the above generalization is able to model long memory, as well as its classical competitor, the fractionally differenced Gegenbauer process, does. In addition, the GHW process does not require the estimation of the memory parameter, simplifying the issue of how to disentangle long memory from a (moderately persistent) short memory component. This leads to a clear advantage of our formulation over the fractional long memory approach.

scholarly journals On nonparametric regression for bivariate circular long-memory time series

2021 ◽  
Author(s):  
Jan Beran ◽  
Britta Steffens ◽  
Sucharita Ghosh
Keyword(s):  
Time Series ◽  
Nonparametric Regression ◽  
Long Range ◽  
Long Memory ◽  
Regression Function ◽  
Confidence Bands ◽  
Long Range Dependence ◽  
Asymptotic Results ◽  
Memory Time ◽  
Circular Time Series

AbstractWe consider nonparametric regression for bivariate circular time series with long-range dependence. Asymptotic results for circular Nadaraya–Watson estimators are derived. Due to long-range dependence, a range of asymptotically optimal bandwidths can be found where the asymptotic rate of convergence does not depend on the bandwidth. The result can be used for obtaining simple confidence bands for the regression function. The method is illustrated by an application to wind direction data.

Power-law correlations, related models for long-range dependence and their simulation

2000 ◽  
Vol 37 (04) ◽  
pp. 1104-1109 ◽  
Author(s):  
Tilmann Gneiting
Keyword(s):  
Long Range ◽  
Power Law ◽  
Long Memory ◽  
Stationary Time Series ◽  
Long Range Dependence ◽  
Short Term ◽  
Permissible Range ◽  
Simultaneous Fitting ◽  
Straightforward Proof

Martin and Walker ((1997) J. Appl. Prob. 34, 657–670) proposed the power-law ρ(v) = c|v|-β, |v| ≥ 1, as a correlation model for stationary time series with long-memory dependence. A straightforward proof of their conjecture on the permissible range of c is given, and various other models for long-range dependence are discussed. In particular, the Cauchy family ρ(v) = (1 + |v/c|α)-β/α allows for the simultaneous fitting of both the long-term and short-term correlation structure within a simple analytical model. The note closes with hints at the fast and exact simulation of fractional Gaussian noise and related processes.

scholarly journals Inconsistencies in repeated refugee status decisions

2019 ◽  
Author(s):  
Philip Pärnamets ◽  
Alexander Tagesson ◽  
Annika Wallin
Keyword(s):  
Asylum Seekers ◽  
Civil Servant ◽  
Affective Responses ◽  
Significant Decline ◽  
Refugee Status ◽  
Seeking Safety ◽  
Active Regulation ◽  
Governmental Intervention ◽  
Emotional Demands ◽  
Over Time

Consistency in civil servant decisions is paramount to upholding judicial equality for citizens and individuals seeking safety through governmental intervention. We investigated refugee status decisions made by a sample of civil servants at the Swedish Migration Agency. We hypothesized, based on the emotional demands such decisions bring with them, that participants would exhibit a compassion fade effect such that refugee status was less likely to be granted over time. To test this, we administered a questionnaire containing brief presentations of asylum seekers and asked participants to judge how likely they would be to give refugee status to the person. Crucially the first, middle and final case presented were matched on decision relevant characteristics. Consistent with our hypothesis we saw a significant decline in ratings. These effects were accentuated by the amount of time a participant had worked at the agency, consistent with depletion of affective resources, and attenuated in workers with greater responsibility and additional training. We conclude that active regulation of empathic and affective responses to asylum seekers may play a role in determining the outcome in refugee status decisions.

Neural networks of data inhibiting long memory pattern

1998 ◽  
Vol 35 (3-4) ◽  
pp. 551-554
Author(s):  
Masood A. Badri ◽  
Ahmed Al-Mutawa ◽  
Amr Murtagy
Keyword(s):  
Neural Networks ◽  
Long Memory ◽  
Memory Pattern
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