scholarly journals A Regionalised Neyman-Scott Model of Rainfall with Convective and Stratiform Cells

1997 ◽  
Vol 1 (1) ◽  
pp. 71-80 ◽  
Author(s):  
P. S. P. Cowpertwait ◽  
P. E. O'Connell
Keyword(s):  
Cluster Model ◽  
Regression Models ◽  
Parameter Estimates ◽  
Model Parameter ◽  
Lack Of Fit ◽  
Dependent Variables ◽  
The Uk ◽  
Poisson Cluster ◽  
Residual Errors ◽  
Urban Sites

Abstract. A single-site Neyman-Scott Poisson cluster model of rainfall, with convective and stratiform cells, is fitted to data for 112 sites scattered throughout the UK using harmonic variables to account for seasonality. The model is regionalised by regressing the estimates of the harmonic variables on site dependent variables (e.g. altitude) to enable rainfall to be simulated at any ungauged site in the UK. An assessment of the residual errors indicates that the regression models can be used with reasonable confidence for urban sites. Furthermore, the regional variations of the model parameter estimates are found to be in agreement with meteorological knowledge and observation. Simulated I h extreme rainfalls are found to compare favourably with observed historical values, although some lack-of-fit is evident for higher aggregation levels.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

scholarly journals The Influence of Industrial Clusters and Place on Innovation and Entrepreneurial Behaviour

2007 ◽  
Vol 8 (3) ◽  
pp. 165-174 ◽  
Author(s):  
Pam McRae-Williams ◽  
Julian Lowe ◽  
Peter Taylor
Keyword(s):  
Regression Models ◽  
Personal Characteristics ◽  
Industrial Clusters ◽  
Factor Scores ◽  
Standard View ◽  
Behaviour Factor ◽  
Regional Clusters ◽  
Entrepreneurial Behaviour ◽  
Dependent Variables ◽  
Central Result

Responses from a questionnaire survey of wine and tourism businesses operating in regional clusters were analysed using factor analysis. These suggested three factor scores relating to entrepreneurial behaviour; four factor scores relating to cluster activities and attributes; and three factors relating to the respondents' personal characteristics. The three entrepreneurial behaviour factor scores were interpreted as: innovator, calculator and venturer. These were used as dependent variables in regression models. The independent variables were the cluster and personal characteristics factor scores, industry and place. The central result was that the cluster activity variables did not have a significant impact on the innovator behaviour variable, which contradicts the standard view. Cluster activities and attributes were found to attract entrepreneurs of the calculator kind, and to a lesser extent, of the venturer kind. Place did seem to offer an attraction to entrepreneurs beyond those offered by the intensities of the cluster activities and attributes.

Optimized blood sampling protocols and sequential design of kinetic experiments

1981 ◽  
Vol 240 (5) ◽  
pp. R259-R265 ◽  
Author(s):  
J. J. DiStefano
Keyword(s):  
Endocrine System ◽  
Primary Objective ◽  
Blood Sampling ◽  
Optimal Designs ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Reverse T3 ◽  
Model Parameter ◽  
Maximum Accuracy ◽  
Sampling Protocols

Design of optimal blood sampling protocols for kinetic experiments is discussed and evaluated, with the aid of several examples--including an endocrine system case study. The criterion of optimality is maximum accuracy of kinetic model parameter estimates. A simple example illustrates why a sequential experiment approach is required; optimal designs depend on the true model parameter values, knowledge of which is usually a primary objective of the experiment, as well as the structure of the model and the measurement error (e.g., assay) variance. The methodology is evaluated from the results of a series of experiments designed to quantify the dynamics of distribution and metabolism of three iodothyronines, T3, T4, and reverse-T3. This analysis indicates that 1) the sequential optimal experiment approach can be effective and efficient in the laboratory, 2) it works in the presence of reasonably controlled biological variation, producing sufficiently robust sampling protocols, and 3) optimal designs can be highly efficient designs in practice, requiring for maximum accuracy a number of blood samples equal to the number of independently adjustable model parameters, no more or less.

scholarly journals The Consequences of Divorce and Splitting up for Spatial Mobility in the UK

2013 ◽  
Vol 38 (2) ◽  
Author(s):  
Peteke Feijten ◽  
Maarten Van Ham
Keyword(s):  
Residential Mobility ◽  
Regression Models ◽  
Disruptive Effect ◽  
British Household Panel Survey ◽  
Union Dissolution ◽  
Panel Survey ◽  
Housing Situation ◽  
Spatial Mobility ◽  
Logistic Regression Models ◽  
The Uk

Union dissolution is well known to have a disruptive effect on the housing situation of those involved, and often leads to downward moves on the “housing ladder”. Much less is known about the geographies of residential mobility after union dissolution. There are, however, reasons to expect that those who experienced a union dissolution have a different likelihood of moving over longer distances than those who stay in a union, because of different moving motives. This study contributes to the existing literature by investigating the occurrences of moves, distances moved and the destinations of moves after union dissolution. The paper also contributes to the literature by investigating the effect on mobility not only of divorce, but also of splitting up and repartnering. Using longitudinal data from the British Household Panel Survey (BHPS), and logistic regression models, we found that union dissolution has a significant effect on the occurrence of moves and on moving distances.

Women in the Legislatures and Executives of the World: Knocking at the Highest Glass Ceiling

1999 ◽  
Vol 51 (4) ◽  
pp. 547-572 ◽  
Author(s):  
Andrew Reynolds
Keyword(s):  
Multivariate Regression ◽  
Regression Models ◽  
Socioeconomic Development ◽  
Party System ◽  
Political Representation ◽  
Parliamentary System ◽  
Dependent Variables ◽  
The World ◽  
Political Office ◽  
Women In Parliament

This article reports the results of a survey of women in legislatures and executives around the world as they were constituted in 1998 (N = 180). The chief hypotheses regarding the factors hindering or facilitating women's access to political representation were tested by multivariate regression models. The regression models juxtaposed a cocktail of institutional, political, cultural, and socioeconomic variables with the following dependent variables: (1) the percentage of MPs who are women and (2) the percentage of cabinet ministers who are women.A number, although not all, of the cited hypotheses were statistically confirmed and more finely quantified. The socioeconomic development of women in society has an effect on the number of women in parliament but not in the cabinet. A country's length of experience with multipartyism and women's enfranchisement correlates with both the legislative and the executive percentage. Certain electoral systems are more women friendly than others. The ideological nature of the party system affects the number of women elected and chosen for cabinet posts. And last, the state's dominant religion, taken as a proxy for culture, also statistically relates to the number of women who will make it to high political office. However, other long-held hypotheses were not proved. The degree of democracy is not a good indicator of the percentage of women who will make it into the legislature or the cabinet, nor is the dichotomy between a presidential or parliamentary system.

A nonparametric lack-of-fit test for heteroscedastic regression models

2011 ◽  
Vol 349 (3-4) ◽  
pp. 215-217
Author(s):  
Jean-Baptiste Aubin ◽  
Samuela Leoni-Aubin
Keyword(s):  
Regression Models ◽  
Lack Of Fit ◽  
Heteroscedastic Regression
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