scholarly journals A comparison of official population projections with Bayesian time series forecasts for England and Wales

2010 ◽  
Vol 141 (1) ◽  
pp. 95-114 ◽  
Author(s):  
Guy J Abel ◽  
Jakub Bijak ◽  
James Raymer
Keyword(s):  
Time Series ◽  
Population Projections ◽  
England And Wales ◽  
Bayesian Time Series

Prison population projections, 2006-2013: England and Wales

2006 ◽  
Author(s):  
Nisha de Silva ◽  
Paul Cowell ◽  
Terence Chow ◽  
Paul Worthington
Keyword(s):  
Prison Population ◽  
Population Projections ◽  
England And Wales

scholarly journals Relationship between daily suicide counts and temperature in England and Wales

2007 ◽  
Vol 191 (2) ◽  
pp. 106-112 ◽  
Author(s):  
Lisa A. Page ◽  
Shakoor Hajat ◽  
R. Sari Kovats
Keyword(s):  
Time Series ◽  
Seasonal Fluctuation ◽  
Daily Temperature ◽  
Short Term ◽  
Time Series Regression ◽  
England And Wales ◽  
Increased Risk ◽  
Hot Weather ◽  
The Impact ◽  
The Relationship

BackgroundSeasonal fluctuation in suicide has been observed in many populations. High temperature may contribute to this, but the effect of short-term fluctuations in temperature on suicide rates has not been studied.AimsTo assess the relationship between daily temperature and daily suicide counts in England and Wales between 1 January 1993 and 31 December 2003 and to establish whether heatwaves are associated with increased mortality from suicide.MethodTime-series regression analysis was used to explore and quantify the relationship between daily suicide counts and daily temperature. The impact of two heatwaves on suicide was estimated.ResultsNo spring or summer peak in suicide was found. Above 18 °, each 1 ° increase in mean temperature was associated with a 3.8 and 5.0% rise in suicide and violent suicide respectively. Suicide increased by 46.9% during the 1995 heatwave, whereas no change was seen during the 2003 heat wave.ConclusionsThere is increased risk of suicide during hot weather.

Differential fertility among immigrants to England and Wales and some implications for population projections

1969 ◽  
Vol 1 (S1) ◽  
pp. 119-127 ◽  
Author(s):  
Jean Thompson
Keyword(s):  
Age Structure ◽  
Age Groups ◽  
Population Projections ◽  
Fertility Rates ◽  
Female Population ◽  
Differential Fertility ◽  
England And Wales ◽  
Adult Age ◽  
Completed Family Size ◽  
Socio Economic Factors

SummaryThe age structure of the immigrant female population as shown by the 1961 Census was heavily biased towards the young adult age groups, where fertility rates are highest. The birth rate for such a population could be expected considerably to exceed the average for this country as a whole, due to differences in age structure alone. The Census also showed marked differences betwen the fertility rates of different groups of immigrants but suggested that for the most important groups —from the Irish Republic, the Indian sub-continent and the Caribbean—they then amounted to a completed family size of roughly ½ child above the England and Wales average. There were also marked differences in 1961 between the socio-economic structure of immigrant groups; such evidence as there is points to socio-economic factors as playing an important part in explaining the fertility of immigrants, and its possible change over time.

scholarly journals Bayesian Time Series Modelling of the Italian Daily Rainfall Data using Mixed Distribution

2019 ◽  
Vol 8 (4) ◽  
pp. 2279-2288
Keyword(s):  
Time Series ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Seasonal Effects ◽  
Model Parameters ◽  
Daily Rainfall Data ◽  
Mixed Distribution ◽  
Time Series Modelling ◽  
Bayesian Time Series ◽  
The Ideal

A combination of continuous and discrete elements is referred to as a mixed distribution. For example, daily rainfall data consist of zero and positive values. We aim to develop a Bayesian time series model that captures the evolution of the daily rainfall data in Italy, focussing on directly linking the amount and occurrence of rainfall. Two gamma (G1 and G2) distributions with different parameterisations and lognormal distribution were investigated to identify the ideal distribution representing the amount process. Truncated Fourier series was used to incorporate the seasonal effects which captures the variability in daily rainfall amounts throughout the year. A first-order Markov chain was used to model rainfall occurrence conditional on the presence or absence of rainfall on the previous day. We also built a hierarchical prior structure to represent our subjective beliefs and capture the initial uncertainties of the unknown model parameters for both amount and occurrence processes. The daily rainfall data from Urbino rain gauge station in Italy were then used to demonstrate the applicability of our proposed methods. Residual analysis and posterior predictive checking method were utilised to assess the adequacy of model fit. In conclusion, we clearly found that our proposed method satisfactorily and accurately fits the Italian daily rainfall data. The gamma distribution was found to be the ideal probability density function to represent the amount of daily rainfall.

scholarly journals Advances in Bayesian Time Series Modeling and the Study of Politics: Theory Testing, Forecasting, and Policy Analysis

2006 ◽  
Vol 14 (1) ◽  
pp. 1-36 ◽  
Author(s):  
Patrick T. Brandt ◽  
John R. Freeman
Keyword(s):  
Time Series ◽  
Policy Analysis ◽  
Theory Testing ◽  
Multiple Time ◽  
Shape Error ◽  
Time Series Modeling ◽  
International Conflicts ◽  
Bayesian Approaches ◽  
Recent Developments ◽  
Bayesian Time Series

Bayesian approaches to the study of politics are increasingly popular. But Bayesian approaches to modeling multiple time series have not been critically evaluated. This is in spite of the potential value of these models in international relations, political economy, and other fields of our discipline. We review recent developments in Bayesian multi-equation time series modeling in theory testing, forecasting, and policy analysis. Methods for constructing Bayesian measures of uncertainty of impulse responses (Bayesian shape error bands) are explained. A reference prior for these models that has proven useful in short- and medium-term forecasting in macroeconomics is described. Once modified to incorporate our experience analyzing political data and our theories, this prior can enhance our ability to forecast over the short and medium terms complex political dynamics like those exhibited by certain international conflicts. In addition, we explain how contingent Bayesian forecasts can be constructed, contingent Bayesian forecasts that embody policy counterfactuals. The value of these new Bayesian methods is illustrated in a reanalysis of the Israeli-Palestinian conflict of the 1980s.

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