Is There Convergence in National Alcohol Consumption Patterns? Evidence from a Compositional Time Series Approach

2018 ◽  
Vol 13 (1) ◽  
pp. 92-98 ◽  
Author(s):  
Terence C. Mills
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Alcohol Consumption ◽  
Statistical Approach ◽  
Consumption Patterns ◽  
Data Sets ◽  
Share Data ◽  
Time Series Approach ◽  
Global Mean ◽  
Jel Classifications

AbstractHolmes and Anderson (2017a) introduce two extensive data sets on world alcohol consumption and expenditure and with them investigate, among other things, the possible convergence of national alcohol consumption patterns using wine, beer, and spirit shares. Such share data define a composition, on which conventional statistical analysis using covariances and correlations is invalid. This note reanalyses the data using techniques appropriate for a composition and introduces a statistic that can validly track the variation in national shares around the global mean through time. This variability statistic shows that such convergence of national alcohol patterns has clearly taken place over the period 1961 to 2014 and thus confirms Holmes and Anderson's findings using a valid statistical approach. (JEL Classifications: C18, D12, L66)

scholarly journals Towards Reliable Probabilistic Time-Series Projections of Global Mean Surface Temperature

2021 ◽  
Author(s):  
Philip G. Sansom ◽  
Donald Cummins ◽  
Stefan Siegert ◽  
David B Stephenson
Keyword(s):  
Time Series ◽  
Global Warming ◽  
Surface Temperature ◽  
Climate Model ◽  
Future Projections ◽  
Perfect Model ◽  
Global Mean Surface Temperature ◽  
Time Series Approach ◽  
Energy Balance Models ◽  
Global Mean

Abstract Quantifying the risk of global warming exceeding critical targets such as 2.0 ◦ C requires reliable projections of uncertainty as well as best estimates of Global Mean Surface Temperature (GMST). However, uncertainty bands on GMST projections are often calculated heuristically and have several potential shortcomings. In particular, the uncertainty bands shown in IPCC plume projections of GMST are based on the distribution of GMST anomalies from climate model runs and so are strongly determined by model characteristics with little influence from observations of the real-world. Physically motivated time-series approaches are proposed based on fitting energy balance models (EBMs) to climate model outputs and observations in order to constrain future projections. It is shown that EBMs fitted to one forcing scenario will not produce reliable projections when different forcing scenarios are applied. The errors in the EBM projections can be interpreted as arising due to a discrepancy in the effective forcing felt by the model. A simple time-series approach to correcting the projections is proposed based on learning the evolution of the forcing discrepancy so that it can be projected into the future. This approach gives reliable projections of GMST when tested in a perfect model setting. When applied to observations this leads to projected warming of 2.2 ◦ C (1.7 ◦ C to 2.9 ◦ C) in 2100 compared to pre-industrial conditions, 0.4 ◦ C lower than a comparable IPCC anomaly estimate. The probability of staying below the critical 2.0 ◦ C warming target in 2100 more than doubles to 0.28 compared to only 0.11 from a comparably IPCC estimate.

The GravIS Portal: User-friendly Global Mass Variations from GRACE and GRACE-FO

2021 ◽  
Author(s):  
Christoph Dahle ◽  
Eva Boergens ◽  
Henryk Dobslaw ◽  
Andreas Groh ◽  
Ingo Sasgen ◽  
...  
Keyword(s):  
Time Series ◽  
Information Service ◽  
Research Centre ◽  
Data Sets ◽  
Ocean Bottom ◽  
Climatic Regions ◽  
Uncertainty Estimates ◽  
Terrestrial Water ◽  
User Friendly ◽  
Global Mean

<p>The German Research Centre for Geosciences (GFZ) maintains the “Gravity Information Service” (GravIS, gravis.gfz-potsdam.de) portal in collaboration with the Alfred-Wegener-Institute (AWI) and Technische Universität Dresden. Main objective of this portal is the dissemination of data describing mass variations in the Earth system based on observations of the satellite gravimetry missions GRACE and GRACE-FO.</p><p>The provided data sets encompass products of terrestrial water storage (TWS) variations over the continents, ocean bottom pressure (OBP) variations from which global mean barystatic sea-level rise can be estimated, and mass changes of the ice sheets in Greenland and Antarctica. All data sets are provided as time series of regular grids for each area, as well as in the form of regional basin averages. Regarding the latter, for the continental TWS data the user can choose between classical river basins and a novel segmentation based on climatic regions. For the oceans, the segmentation into different regions is derived similarly but based on modelled OBP data. All time series are accompanied by realistic uncertainty estimates.</p><p>All data sets can be interactively displayed at the portal and are freely available for download. This contribution aims to show the features and possibilities of the GravIS portal to researchers without a dedicated geodetic background, working in the fields of hydrology, oceanography, and cryosphere.</p>

Statistical Analysis and Evaluation of Crime Committed by Inmates in Benin Prison in Edo State using Time Series Model

2018 ◽  
Vol 8 (4) ◽  
pp. 24
Author(s):  
Ogbeide, E. Michael ◽  
Sarah, O. Elakhe
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Crime Rate ◽  
Time Series Model ◽  
Suitable Model ◽  
Rate Data ◽  
Analysis And Evaluation ◽  
Benin City ◽  
Time Series Approach ◽  
Edo State

Crimes exist in every society. This paper presents the statistical analysis of crime committed Inmates in Benin City Prison in Edo State with a suitable model using a time series approach. The paper examines the extent of crime committed in the prison for a period of seven years between 1999 to 2005. The study showedsss that age has no influence on the type of crime committed and that religion has no influence on the crime rate. The presentation gives future forecast in the population of prisoners in the prison with available crime rate data.

scholarly journals A new statistical approach to model the counts of novel coronavirus cases

2020 ◽  
Author(s):  
M. El-Morshedy ◽  
Emrah Altun ◽  
M. S. Eliwa
Keyword(s):  
Risk Factors ◽  
Air Pollution ◽  
Alcohol Consumption ◽  
Statistical Approach ◽  
Discrete Distribution ◽  
Oecd Countries ◽  
Data Sets ◽  
Statistical Tools ◽  
Novel Coronavirus ◽  
Two Parameter

Abstract This study proposes new statistical tools to analyze the counts of the daily coronavirus cases and deaths. Since the daily new cases and deaths exhibit highly overdispersion, we introduce a new two-parameter discrete distribution, called \textit{discrete generalized Lindley}, which enables us to model all kinds of dispersion such as under, equi and overdispersion. Additionally, we introduce a new count regression model based on the proposed distribution to investigate the effects of the important risk factors on the counts of deaths for OECD countries. Three data sets are analyzed with proposed models and competitive models. Empirical findings show that air pollution, the proportion of obesity, and smokers in a population do not affect the counts of deaths for OECD countries. The interesting empirical result is that the countries with having larger alcohol consumption have lower counts of deaths.

Alcohol consumption patterns in heavy drinkers with and without alcoholic liver disease (ALD)

2001 ◽  
Vol 120 (5) ◽  
pp. A117-A117
Author(s):  
K DEAR ◽  
M BRADLEY ◽  
K MCCORMACK ◽  
R PECK ◽  
D GLEESON
Keyword(s):  
Liver Disease ◽  
Alcohol Consumption ◽  
Alcoholic Liver Disease ◽  
Consumption Patterns ◽  
Heavy Drinkers

Delivering Sustainable Water Systems Using Kalman Filter and Statistical Approach

2017 ◽  
Vol 4 (1) ◽  
pp. 41-52
Author(s):  
Dedy Loebis
Keyword(s):  
Kalman Filtering ◽  
Statistical Approach ◽  
Water Systems ◽  
Data Sets ◽  
Pressure Data ◽  
Burst Event ◽  
Sample Data ◽  
Other Information ◽  
Supply Systems ◽  
Frequency Features

This paper presents the results of work undertaken to develop and test contrasting data analysis approaches for the detection of bursts/leaks and other anomalies within wate r supply systems at district meter area (DMA)level. This was conducted for Yorkshire Water (YW) sample data sets from the Harrogate and Dales (H&D), Yorkshire, United Kingdom water supply network as part of Project NEPTUNE EP/E003192/1 ). A data analysissystem based on Kalman filtering and statistical approach has been developed. The system has been applied to the analysis of flow and pressure data. The system was proved for one dataset case and have shown the ability to detect anomalies in flow and pres sure patterns, by correlating with other information. It will be shown that the Kalman/statistical approach is a promising approach at detecting subtle changes and higher frequency features, it has the potential to identify precursor features and smaller l eaks and hence could be useful for monitoring the development of leaks, prior to a large volume burst event.

scholarly journals Interpretation of the Chemical and Physical Time-Series Retrieved from Sentik Glacier, Ladakh Himalaya, India

1984 ◽  
Vol 30 (104) ◽  
pp. 66-76 ◽  
Author(s):  
Paul A. Mayewski ◽  
W. Berry Lyons ◽  
N. Ahmad ◽  
Gordon Smith ◽  
M. Pourchet
Keyword(s):  
Time Series ◽  
Chemical Species ◽  
Data Sets ◽  
Reactive Iron ◽  
Physical Time ◽  
Ladakh Himalaya ◽  
Data Density ◽  
Mass Circulation ◽  
The Himalaya ◽  
Analysis Of Time Series

AbstractSpectral analysis of time series of a c. 17 ± 0.3 year core, calibrated for total ß activity recovered from Sentik Glacier (4908m) Ladakh, Himalaya, yields several recognizable periodicities including subannual, annual, and multi-annual. The time-series, include both chemical data (chloride, sodium, reactive iron, reactive silicate, reactive phosphate, ammonium, δD, δ(18O) and pH) and physical data (density, debris and ice-band locations, and microparticles in size grades 0.50 to 12.70 μm). Source areas for chemical species investigated and general air-mass circulation defined from chemical and physical time-series are discussed to demonstrate the potential of such studies in the development of paleometeorological data sets from remote high-alpine glacierized sites such as the Himalaya.

Sign in / Sign up

Export Citation Format

Share Document