Temporal stability of model parameters in crime rate analysis: An empirical examination

2015 ◽  
Vol 58 ◽  
pp. 141-152 ◽  
Author(s):  
Li He ◽  
Antonio Páez ◽  
Desheng Liu ◽  
Shiguo Jiang
Keyword(s):  
Crime Rate ◽  
Temporal Stability ◽  
Model Parameters ◽  
Empirical Examination ◽  
Rate Analysis

Instrumental and Ideological Union Commitment: Longitudinal Assessment of Construct Validity

2001 ◽  
Vol 17 (2) ◽  
pp. 98-111 ◽  
Author(s):  
Anders Sjöberg ◽  
Magnus Sverke
Keyword(s):  
Construct Validity ◽  
Temporal Stability ◽  
Strong Support ◽  
Internal Consistency Reliability ◽  
Measurement Model ◽  
Two Dimensions ◽  
Model Parameters ◽  
Longitudinal Assessment ◽  
Union Commitment ◽  
Union Participation

Summary: Previous research has identified instrumentality and ideology as important aspects of member attachment to labor unions. The present study evaluated the construct validity of a scale designed to reflect the two dimensions of instrumental and ideological union commitment using a sample of 1170 Swedish blue-collar union members. Longitudinal data were used to test seven propositions referring to the dimensionality, internal consistency reliability, and temporal stability of the scale as well as postulated group differences in union participation to which the scale should be sensitive. Support for the hypothesized factor structure of the scale and for adequate reliabilities of the dimensions was obtained and was also replicated 18 months later. Tests for equality of measurement model parameters and test-retest correlations indicated support for the temporal stability of the scale. In addition, the results were consistent with most of the predicted differences between groups characterized by different patterns of change/stability in union participation status. The study provides strong support for the construct validity of the scale and indicates that it can be used in future theory testing on instrumental and ideological union commitment.

The Temporal Stability of the NBD-Dirichlet Model Parameters

2011 ◽  
Author(s):  
Malcolm Wright ◽  
Lara Stocchi ◽  
Carl Driesener
Keyword(s):  
Temporal Stability ◽  
Model Parameters ◽  
Dirichlet Model

scholarly journals Temporal stability of electrical conductivity in a sandy soil

2016 ◽  
Vol 30 (3) ◽  
pp. 349-357 ◽  
Author(s):  
Aura Pedrera-Parrilla ◽  
Eric C. Brevik ◽  
Juan V. Giráldez ◽  
Karl Vanderlinden
Keyword(s):  
Electrical Conductivity ◽  
Spatial Variability ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Precision Agriculture ◽  
Temporal Stability ◽  
Principal Component ◽  
Model Parameters ◽  
Soil Spatial Variability

Abstract Understanding of soil spatial variability is needed to delimit areas for precision agriculture. Electromagnetic induction sensors which measure the soil apparent electrical conductivity reflect soil spatial variability. The objectives of this work were to see if a temporally stable component could be found in electrical conductivity, and to see if temporal stability information acquired from several electrical conductivity surveys could be used to better interpret the results of concurrent surveys of electrical conductivity and soil water content. The experimental work was performed in a commercial rainfed olive grove of 6.7 ha in the ‘La Manga’ catchment in SW Spain. Several soil surveys provided gravimetric soil water content and electrical conductivity data. Soil electrical conductivity values were used to spatially delimit three areas in the grove, based on the first principal component, which represented the time-stable dominant spatial electrical conductivity pattern and explained 86% of the total electrical conductivity variance. Significant differences in clay, stone and soil water contents were detected between the three areas. Relationships between electrical conductivity and soil water content were modelled with an exponential model. Parameters from the model showed a strong effect of the first principal component on the relationship between soil water content and electrical conductivity. Overall temporal stability of electrical conductivity reflects soil properties and manifests itself in spatial patterns of soil water content.

Modelling the individual and collective dynamics of the propensity to offend

2010 ◽  
Vol 21 (4-5) ◽  
pp. 421-440 ◽  
Author(s):  
J.-P. NADAL ◽  
M. B. GORDON ◽  
J. R. IGLESIAS ◽  
V. SEMESHENKO
Keyword(s):  
Crime Rate ◽  
Developed Countries ◽  
Wide Distribution ◽  
Deterrent Effect ◽  
Model Parameters ◽  
Self Organized ◽  
Interacting Agents ◽  
Composite Parameter ◽  
Two Phases ◽  
The Individual

We introduce a general framework for modelling the dynamics of the propensity to offend in a population of (possibly interacting) agents. We consider that each agent has an ‘honesty index’ which parameterizes his probability of abiding by the law. This probability also depends on a composite parameter associated to the attractiveness of the crime outcome and of the crime setting (the context which makes a crime more or less likely to occur, such as the presence or not of a guardian). Within this framework we explore some consequences of the working hypothesis that punishment has a deterrent effect, assuming that, after a criminal act, an agent's honesty index may increase if he is caught and decrease otherwise. We provide both analytical and numerical results. We show that in the space of parameters characterizing the probability of punishment, there are two ‘phases’: one corresponding to a population with a low crime rate and the other to a population with a large crime rate. We speculate on the possible existence of a self-organized state in which, due to the society reaction against crime activities, the population dynamics would be stabilized on the critical line, leading to a wide distribution of propensities to offend in the population. In view of empirical works on the causes of the recent evolution of crime rates in developed countries, we discuss how changes of socio-economic conditions may affect the model parameters, and hence the crime rate in the population. We suggest possible extensions of the model that will allow us to take into account more realistic features.

Modelling Pedestrian Movement to Measure On-Street Crime Risk

2011 ◽  
pp. 71-91 ◽  
Author(s):  
Spencer Chainey ◽  
Jake Desyllas
Keyword(s):  
Crime Rate ◽  
Local Level ◽  
Crime Rates ◽  
Street Crime ◽  
Accurate Analysis ◽  
Pedestrian Movement ◽  
Rate Analysis ◽  
Large Scale Analysis ◽  
Residential Population ◽  
Crime Risk

This chapter presents results for the first large-scale analysis of street crime rates that utilizes accurate on-street pedestrian population estimates. Pedestrian counts were generated at the street segment level for an area in central London (UK) using a modeling process that utilized key indicators of pedestrian movement and sample observations. Geocoded street crime positioned on street segments then allowed for street crime rates to be calculated for the entire central London study area’s street network. These street crime rate measures were then compared against street crime volume patterns (e.g., hotspot maps of street crime density) and street crime rate statistics and maps that were generated from using the residential population as the denominator. The research demonstrates the utility of pedestrian modeling for generating better and more realistic measures for street crime rates, suggesting that if the residential population is used as a denominator for local level street crime analysis it may only misinform and mislead the interpretation and understanding of on- to pedestrians. The research also highlights the importance of crime rate analysis for understanding and explaining crime patterns, and suggests that with accurate analysis of crime rates, policing, and crime prevention initiatives can be improved.

scholarly journals Stability and Change in Diffusion Model Parameters over Two Years

2021 ◽  
Vol 9 (2) ◽  
pp. 26
Author(s):  
Mischa von Krause ◽  
Stefan T. Radev ◽  
Andreas Voss ◽  
Martin Quintus ◽  
Boris Egloff ◽  
...  
Keyword(s):  
Individual Differences ◽  
Diffusion Model ◽  
Processing Speed ◽  
Rank Order ◽  
Temporal Stability ◽  
Model Parameters ◽  
Stability And Change ◽  
Trade Offs ◽  
Time Period ◽  
Speed Accuracy

In recent years, mathematical models of decision making, such as the diffusion model, have been endorsed in individual differences research. These models can disentangle different components of the decision process, like processing speed, speed–accuracy trade-offs, and duration of non-decisional processes. The diffusion model estimates individual parameters of cognitive process components, thus allowing the study of individual differences. These parameters are often assumed to show trait-like properties, that is, within-person stability across tasks and time. However, the assumption of temporal stability has so far been insufficiently investigated. With this work, we explore stability and change in diffusion model parameters by following over 270 participants across a time period of two years. We analysed four different aspects of stability and change: rank-order stability, mean-level change, individual differences in change, and profile stability. Diffusion model parameters showed strong rank-order stability and mean-level changes in processing speed and speed–accuracy trade-offs that could be attributed to practice effects. At the same time, people differed little in these patterns across time. In addition, profiles of individual diffusion model parameters proved to be stable over time. We discuss implications of these findings for the use of the diffusion model in individual differences research.

scholarly journals A Comparison of Generalized Hyperbolic Distribution Models for Equity Returns

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Virginie Konlack Socgnia ◽  
Diane Wilcox
Keyword(s):  
Stock Returns ◽  
Goodness Of Fit ◽  
Temporal Stability ◽  
Information Criterion ◽  
Estimation Algorithm ◽  
Dependence Structure ◽  
Model Parameters ◽  
Distribution Models ◽  
Generalized Hyperbolic Distribution ◽  
Fit Statistics

We discuss the calibration of the univariate and multivariate generalized hyperbolic distributions, as well as their hyperbolic, variance gamma, normal inverse Gaussian, and skew Student’st-distribution subclasses for the daily log-returns of seven of the most liquid mining stocks listed on the Johannesburg Stocks Exchange. To estimate the model parameters from historic distributions, we use an expectation maximization based algorithm for the univariate case and a multicycle expectation conditional maximization estimation algorithm for the multivariate case. We assess the goodness of fit statistics using the log-likelihood, the Akaike information criterion, and the Kolmogorov-Smirnov distance. Finally, we inspect the temporal stability of parameters and note implications as criteria for distinguishing between models. To better understand the dependence structure of the stocks, we fit the MGHD and subclasses to both the stock returns and the two leading principal components derived from the price data. While the MGHD could fit both data subsets, we observed that the multivariate normality of the stock return residuals, computed by removing shared components, suggests that the departure from normality can be explained by the structure in the common factors.

scholarly journals Spatiotemporal variability of soil-water characteristic curve model parameters of Lanzhou collapsible loess

2021 ◽  
Author(s):  
Wenju Zhao ◽  
Yuhang Liu ◽  
Jiazhen Hu ◽  
Zongli Li
Keyword(s):  
Soil Water ◽  
Characteristic Curve ◽  
Temporal Stability ◽  
Spatiotemporal Variability ◽  
Model Parameters ◽  
Measuring Point ◽  
Collapsible Loess ◽  
Comprehensive Comparison ◽  
The Mean ◽  
Relative Differences

Abstract The spatiotemporal variation of the model parameters of the soil-water characteristic curve (SWCC) reflect the soil water holding capacity and soil pore distribution state. It is an integral part of interdisciplinary disciplines such as soil hydrodynamics and ecohydrology. The authors selected the optimal SWCC model for the Lanzhou collapsible loess, used classical statistics and geostatistics methods studied the spatiotemporal variability of the SWCC model parameters, and used the comprehensive comparison of the mean relative differences (MRD), standard deviations (SDRD) and an index of temporal stability (ITS) determined the representativeness measuring point. The results showed that the SWCC parameters α was medium variability in the 0–30 cm soil layer, n and θs were of low variability, the spatial distribution of the parameters of different soil layers was consistent. Migration direction prediction of θs was very similar in each layer, α, n and θs were all strongly significantly correlated positively. Moreover, the determination coefficient of representative measuring point 16 had the highest prediction accuracy for the measured values of SWCC. The results of this paper can be used as a simple method to predict SWCC and provide theoretical guidance for soil water management and soil collapse erosion monitoring in collapsible loess area. HIGHLIGHT Presented a study of the temporal stability and variability of SWCC in the Lanzhou collapsible loess, using the comprehensive comparison of the Mean relative differences (MRD), standard deviations (SDRD) and an index of temporal stability (ITS), and determined the representativeness measuring point.

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