Statistical modelling of international migration flows

The paper deals with uncertainty in estimating international migration flows for an interlinked system of countries. The related problems are discussed on the example of a dedicated model 'IMEM' (Integrated Model of European Migration). The IMEM is a hierarchical Bayesian model, which allows for combining data from different countries with meta-data on definitions and collection methods, as well as with relevant expert information. The model is applied to 31 EU and EFTA countries for the period 2002–2008. The expert opinion comes from a two-round Delphi survey carried out amongst 11 European experts on issues related to migration statistics. The adopted Bayesian approach allows for a coherent quantification of uncertainty stemming from different sources (data discrepancies, model parameters, and expert judgement). The outcomes produced by the model – whole posterior distributions of estimated flows – can be then used for assessing the true magnitude of flows at the European level, taking into account relative costs of overestimating or underestimating of migration flows. In this context, problems related to application of the decision statistical analysis to multidimensional problems are briefly discusse

Inclusions of Waterman-Shiba spaces into generalized Wiener classes

The characterization of the inclusion of Waterman-Shiba spaces $\Lambda BV^{(p)}$ into generalized Wiener classes of functions $BV(q;\,\delta)$ is given. It uses a new and shorter proof and extends an earlier result of U. Goginava.Comment: 5 page

Pass Permitting Movement on the Terrain of Military Operations for May 1944

Pass permitting movement on the terrain of military operations for May 1944. In Polish. Italy.https://digitalcommons.buffalostate.edu/drzpasses/1008/thumbnail.jp

Improving estimates of migration flows to Eurostat

In this paper we identify the current mandatory requirements and issues concerning the supply of detailed migration data to Eurostat. Using simple illustrations on immigration to the United Kingdom, we show how substantial and significant improvements can be made to the flows reported by the International Passenger Survey, which contain irregularities and missing data due to its relatively small sample size. Our general methodology is based on the idea of smoothing, repairing and combining data within multiplicative component framework

Confirming the Diagnosis of Amyloidosis

Amyloidosis is a general term for diseases characterised by the deposition of insoluble amyloid fibrils in organs or tissues, leading to organ dysfunction and, in many cases, death. Amyloid fibrils are derived from soluble precursor proteins, with the number of known amyloidogenic proteins increasing over time. The identity of the precursor protein often predicts the disease phenotype, although many of the amyloidoses have overlapping clinical features. Most patients with amyloidosis will require biopsy of an involved organ or tissue to confirm the diagnosis. Cardiac transthyretin amyloidosis, however, may be diagnosed without a biopsy provided stringent criteria are met. Where amyloid is confirmed histologically, the identity of the amyloidogenic protein must be determined, given several of the amyloidoses have disease-specific therapies. Laser capture microdissection and tandem mass spectrometry, LCM-MS, has revolutionised amyloid subtyping, being able to identify the amyloidogenic protein more reliably than antibody-based methods such as immunohistochemistry. Here we summarise the biopsy approach to amyloidosis, as well as the non-biopsy diagnosis of cardiac transthyretin amyloidosis. Proteomic and antibody-based methods for amyloid subtyping are reviewed. Finally, an algorithm for confirming the diagnosis of amyloidosis is presented

Forecasting environmental migration to the United Kingdom, 2010 - 2060: an exploration using Bayesian models

Over the next fifty years the potential impact on human livelihoods of environmental change could be considerable. One possible response may be increased levels of human mobility. This paper offers a first quantification of the levels of environmental migration to the United Kingdom that might be expected. The authors apply Bijak and Wi?niowski’s (2010) methodology for forecasting migration using Bayesian models. They seek to advance the conceptual understanding of forecasting in three ways. First, the paper is believed to be the first time that the Bayesian modelling approach has been attempted in relation to environmental mobility. Second, the paper examines the plausibility of Bayesian modelling of UK immigration by cross-checking expert responses to a Delphi survey with the expectations about environmental mobility evident in the recent research literature. Third, the values and assumptions of the expert evidence provided in the Delphi survey are interrogated to illustrate the limited set of conditions under which the forecasts of environmental mobility, as set out in this paper, are likely to hold

Augmenting migration statistics with expert knowledge

International migration statistics vary considerably from one country to another in terms of measurement, quality and coverage. Furthermore, immigration tend to be captured more accurately than emigration. In this paper, we first describe the need to augment reported flows of international migration with knowledge gained from experts on the measurement of migration statistics, obtained from a multi-stage Delphi survey. Second, we present our methodology for translating this information into prior distributions for input into the Integrated Modelling of European Migration (IMEM) model, which is designed to estimate migration flows amongst countries in the European Union (EU) and European Free Trade Association (EFTA), by using recent data collected by Eurostat and other national and international institutions. The IMEM model is capable of providing a synthetic data base with measures of uncertainty for international migration flows and other model parameters.

Finding informed trades in high-frequency trading

We propose a mathematical procedure for finding informed trades in high-frequency trading on different financial markets.We formulate criteria for detecting insider trades. These criteria were applied in practice to detect insider trading of Aeroflot shares