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The report provides background information on small scale enterprises in Botswana that received support from the Financial Assistance Policy and identifies special problems the projects have experienced with the FAP

Anthony Amsterdam urged litigators and scholars to focus on individual prosecutors' offices or counties and to identify "a set of local institutions, conventions, and practices which are manifestly the residues of classic Southern apartheid"; to "conduct analyses of the impact of race in the sentencing patterns . . . in those specific counties or venues"; and to "investigate, analyze, and prepare evidence of the legacy of apartheid embedded in the counties' political, economic, and social life, particularly as it bears on law enforcement, prosecution, and courthouse customs." The goal, Amsterdam says, is "to build a case not solely on statistical evidence of discrimination but to supplement it with evidence of anecdotes and local custom." Hamilton County, Ohio, lies technically just north of the South, but it is close. Its history reflects the emblematic segregation and overt racism associated with the South. This paper documents this history. It also remains in the top 2% of counties producing a majority of executions nationally. This history and ongoing use of the death penalty made it an ideal candidate for the kind of hyper-localized inquiry that Amsterdam suggested. This article reports a study of all cases charged with aggravated murder in Hamilton County from January 1992 to August 2017, including controlled analyses on three outcome measures. The model for the prosecutor's decision to charge a case capitally showed, after taking into account potentially relevant race-neutral factors, that a case with at least one white victim faced odds of being charged capitally that were 4.54 times the odds of a similarly situated case with no white victims. The model of the decision to impose a death sentence overall (combining the charging and sentencing decisions) found that a black defendant who killed at least one white victim faced odds of receiving a death sentence that were 3.79 times those of all other similarly situated defendants. Finally, in a model of the death sentencing decisions limited to death-specified cases (that is, the cases in which the state sought death), a black defendant with at least one white victim faced odds of receiving a death sentence that were 5.33 higher than all other cases. These findings are both theoretically and statistically significant (p < .01). The local practice and history, bolstered by the statistical analysis, makes a strong case that race has influenced the administration of capital punishment in Hamilton County, Ohio.

Appendixes: A. Economic conference of the allied governments.--B. Report of British Committee on commercial and industrial policy after the war.--C. Imports and exports (temporary control) bill.--D. The British nonferrous metal industry act. ; At head of title: Department of commerce. William C. Redfield, secretary. Bureau of foreign and domestic commerce. B. S. Cutler, chief. ; Mode of access: Internet.

This book provides a broad introduction to the fascinating subject of environmental space-time processes, addressing the role of uncertainty. Within that context, it covers a spectrum of technical matters from measurement to environmental epidemiology to risk assessment. It showcases non-stationary vector-valued processes, while treating stationarity as a special case. The contents reflect the authors cumulative knowledge gained over many years of consulting and research collaboration. In particular, with members of their research group, they developed within a hierarchical Bayesian framework, the new statistical approaches presented in the book for analyzing, modeling, and monitoring environmental spatio-temporal processes. Furthermore they indicate new directions for development.This book contains technical and non-technical material and it is written for statistical scientists as well as consultants, subject area researchers and students in related fields. Novel chapters present the authors hierarchical Bayesian approaches to:- spatially interpolating environmental processes- designing networks to monitor environmental processes- multivariate extreme value theory- incorporating risk assessmentIn addition, they present a comprehensive and critical survey of other approaches, highlighting deficiencies that their method seeks to overcome. Special sections marked by an asterisk provide rigorous development for readers with a strong technical background. Alternatively readers can go straight to the tutorials supplied in chapter 14 and learn how to apply the free, downloadable modeling and design software that the authors and their research partners have developed.

This selection of articles emerged from different works presented "The Art of Semiparametrics" conference in 2003 in Berlin. It offers a collection of individual works that together show the large spectrum of semiparametric statistics. The book combines theoretical contributions with more applied and empirical studies. Although each article represents an original contribution to its own field, all are written in a self-contained way that may be read by non-experts.

The Fifth International Workshop on Model-Oriented Data Analysis (MODA5) focused on experimental design, particularly optimum design. A strength of this series of workshops is that they bring together leading scientists from "Eastern" and "Western" Europe. The proceedings therefore provides a valuable reference to the work of groups from many countries. In addition to 11 papers on optimum designs for linear and nonlinear models, there are groups of papers on designs for quality improvement, designs in agriculture and for model building. Non-design problems include robustness in linear models and estimation problems in nonlinear models. The volume concludes with a discussion on the teaching of experimental design

Part I: Advanced Statistical and Mathematical Methods for Time Series Analysis -- Random Forest Variable Selection for Sparse Vector Autoregressive Models (Dmitry Pavlyuk) -- Covariance functions for Gaussian Laplacian fields in higher dimension (Gyorgy Terdik) -- The Correspondence between Stochastic Linear Diference and Diferential Equations (D. Stephen G. Pollock) -- New test for a random walk detection based on the arcsine law (Konrad Furmanczyk, Marcin Dudzinski and Arkadiusz Orlowski) -- Part II: Econometric Models and Forecasting -- On the automatic identification of Unobserved Components Models (Diego J. Pedregal and Juan R. Trapero) -- Spatial integration of pig meat markets in the EU: Complex Network analysis of nonlinear price relationships (Christos Emmanouilides and Alexej Proskynitopoulos) -- Comparative Study of Models for Forecasting Nigerian Stock Exchange Market Capitalization (Nura Isah, Basiru Yusuf and Sani I.S. Doguwa) -- Industry Specifics of Models Predicting Financial Distress (Dagmar Camska) -- Stochastic volatility model's predictive relevance for Equity Markets (Per B Solibakke) -- Empirical test of the Balassa-Samuelson Effect in Selected African Countries (Joel Hinaunye Eita, Zitsile Zamantungwa Khumalo and Ireen Choga) -- Part III: Energy Time Series Forecasting -- End of charge detection of batteries with high production tolerances (Andre Loechte, Ole Gebert and Peter Gloesekoetter) -- The effect of Daylight Saving Time on Spanish Electrical Consumption (Eduardo Caro Huertas, Jesus Juan Ruiz, Marta Mana Sanchez, Jesus Ruperez Aguilera, Carlos Rodriguez Huidobro, Ana Rodriguez Aparicio and Juan Jose Abellan Perez) -- Wind Speed Forecasting Using Kernel Ridge Regression (Mohammad Alalami, Maher Maalouf and Tarek El Fouly) -- Applying a 1D-CNN Network to Electricity Load Forecasting (Christian Lang, Florian Steinborn, Oliver Steffens and Elmar W. Lang) -- Long and Short Term Prediction of Power Consumption using LSTM Networks (Juan Carlos Morales, Salvador Moreno, Carlos Bailon, Hector Pomares, Ignacio Rojas and Luis Javier Herrera) -- Part IV: Forecasting Complex/Big data problems -- Freedman's Paradox: a Solution Based on Normalized Entropy (Pedro Macedo) -- Mining News Data for the Measurement and Prediction of Inflation Expectations (Diana Gabrielyan, Lenno Uuskula and Jaan Masso) -- Big Data: Forecasting and Control for Tourism Demand (Miguel Angel Ruiz Reina) -- Traffic Networks via Neural Networks: Description and Evolution (Alexandros Sopasakis) -- Part V: Time Series Analysis with Computational Intelligence -- A Comparative Study on Machine Learning Techniques for Intense Convective Rainfall Events Forecasting (Matteo Sangiorgio, Stefano Barindelli, Valerio Guglieri, Riccardo Biondi, Enrico Solazzo, Eugenio Realini, Giovanna Venuti and Giorgio Guariso) -- Long-Short Term Memory Networks for the Prediction of Transformer Temperature for Energy Distribution Smart Grids (Francisco Jesus Martinez-Murcia, Javier Ramirez, Fermin Segovia, Andres Ortiz, Susana Carrillo, Javier Leiva, Jacob Rodriguez-Rivero and Juan Manuel Gorriz) -- Deep Multilayer Perceptron for Knowledge Extraction: Understanding the Gardon de Mialet Flash Floods Modelling (Bob E. Saint Fleur, Guillaume Artigue, Anne Johannet and Severin Pistre) -- Forecasting short-term and medium-term time series:a comparison of artificial neural networks and fuzzy models (Tatiana Afanasieva and Pavel Platov) -- Inflation Rate Forecasting: Extreme Learning Machine as a Model Combination Method (Jeronymo Marcondes Pinto and Emerson Fernandes Marcal) -- Part VI: Time Series Analysis and Prediction in Other Real Problems -- Load Forecast by Multi Task Learning Models: designed for a new collaborative world (Leontina Pinto, Jacques Szczupak and Robinson Semolini) -- Power transformer forecasting in smart grids using NARX neural networks (Javier Ramirez, Francisco J. Martinez Murcia, Fermin Segovia, Andres Ortiz, Diego Salas-Gonz_alez, Susana Carrillo, Javier Leiva, Jacob Rodriguez- Rivero and Juan M. Gorriz) -- Short term forecast of emergency departements visits through calendar selection (Cosimo Lovecchio, Mauro Tucci, Sami Barmada, Andrea Serafini, Luigi Bechi, Mauro Breggia, Simona Dei and Daniela Matarrese) -- Discordant Observation Modelling (Sonya Leech and Bojan Bozic) -- Applying Diebold-Mariano test for performance evaluation between individual and hybrid time series models for modeling bivariate time series data and forecasting the unemployment rate in the USA (Moamen Abbas Mousa Al-Sharifi and Firas Ahmmed Mohammed Al-Mohana).