The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Jeffrey P Prestemon - One of the best experts on this subject based on the ideXlab platform.
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exploiting autoregressive properties to develop prospective urban Arson forecasts by target
Applied Geography, 2013Co-Authors: Jeffrey P Prestemon, David T Butry, Douglas S ThomasAbstract:Abstract Municipal fire departments responded to approximately 53,000 intentionally-set fires annually from 2003 to 2007, according to National Fire Protection Association figures. A disproportionate amount of these fires occur in spatio-temporal clusters, making them predictable and, perhaps, preventable. The objective of this research is to evaluate how the aggregation of data across space and target types (residential, non-residential, vehicle, outdoor and other) affects daily Arson forecast accuracy for several target types of Arson, and the ability to leverage information quantifying the autoregressive nature of intentional firesetting. To do this, we estimate, for the city of Detroit, Michigan, competing statistical models that differ in their ability to recognize potential temporal autoregressivity in the daily count of Arson fires. Spatial units vary from Census tracts, police precincts, to citywide. We find that (1) the out-of-sample performance of prospective hotspot models for Arson cannot usefully exploit the autoregressive properties of Arson at fine spatial scales, even though autoregression is significant in-sample, hinting at a possible bias-variance tradeoff; (2) aggregation of Arson across reported targets can yield a model that differs from by-target models; (3) spatial aggregation of data tends to increase forecast accuracy of Arson due partly to the ability to account for temporally dynamic firesetting; and (4) Arson forecast models that recognize temporal autoregression can be used to forecast daily Arson fire activity at the Citywide scale in Detroit. These results suggest a tradeoff between the collection of high resolution spatial data and the use of more sophisticated modeling techniques that explicitly account for temporal correlation.
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time to burn modeling wildland Arson as an autoregressive crime function
American Journal of Agricultural Economics, 2005Co-Authors: Jeffrey P Prestemon, David T ButryAbstract:Six Poisson autoregressive models of order p [PAR(p)] of daily wildland Arson ignition counts are estimated for five locations in Florida (1994‐2001). In addition, a fixed effects time-series Poisson model of annual Arson counts is estimated for all Florida counties (1995‐2001). PAR(p) model estimates reveal highly significant Arson ignition autocorrelation, lasting up to eleven days, in addition to seasonality and links to law enforcement, wildland management, historical fire, and weather. The annual fixed effects model replicates many findings of the daily models but also detects the influence of wages and poverty on Arson, in ways expected from theory. All findings support an economic model of crime.
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spatio temporal wildland Arson crime functions
Research Papers in Economics, 2005Co-Authors: David T Butry, Jeffrey P PrestemonAbstract:Wildland Arson creates damages to structures and timber and affects the health and safety of people living in rural and wildland urban interface areas. We develop a model that incorporates temporal autocorrelations and spatial correlations in wildland Arson ignitions in Florida. A Poisson autoregressive model of order p, or PAR(p) model, is estimated for six high Arson Census tracts in the state for the period 1994-2001. Spatio-temporal lags of wildland Arson ignitions are introduced as dummy variables indicating the presence of an ignition in previous days in surrounding Census tracts and counties. Temporal lags of ignition activity within the Census tract are shown to be statistically significant and larger than previously reported for non-spatial variants of the PAR(p) model. Spatio-temporal lagged relationships with current Arson that were statistically significant show that Arson activity up to a county away explains Arson patterns, and spatio-temporal lags longer than two days were not significant. Other variables showing significance include weather and wildfire activity in the previous six years, but prescribed fire and several variables that provide evidence that such activity is consistent with an economic model of crime were less commonly significant.
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spatio temporal wildland Arson crime functions
Selected paper presented at the American Agricultural Economics Association Annual Meeting Providence Rhode Island July 24-27 2005: American Agricultu, 2005Co-Authors: David T Butry, Jeffrey P PrestemonAbstract:Wildland Arson creates damages to structures and timber and affects the health and safety of people living in rural and wildland urban interface areas. We develop a model that incorporates temporal autocorrelations and spatial correlations in wildland Arson ignitions in Florida. A Poisson autoregressive model of order p, or PAR(p) model, is estimated for six high Arson Census tracts in the state for the period 1994-2001. Spatio-temporal lags of wildland Arson ignitions are introduced as dummy variables indicating the presence of an ignition in previous days in surrounding Census tracts and counties. Temporal lags of ignition activity within the Census tract are shown to be statistically significant and larger than previously reported for non-spatial variants of the PAR(p) model. Spatio-temporal lagged relationships with current Arson that are statistically significant show that Arson activity up to a county away explains Arson patterns, and spatio-temporal lags longer than two days were not significant. Other variables showing significance include weather and wildfire activity in the previous six years, but prescribed fire and several variables that provide evidence that such activity is consistent with an economic model of crime were less commonly significant.
David T Butry - One of the best experts on this subject based on the ideXlab platform.
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exploiting autoregressive properties to develop prospective urban Arson forecasts by target
Applied Geography, 2013Co-Authors: Jeffrey P Prestemon, David T Butry, Douglas S ThomasAbstract:Abstract Municipal fire departments responded to approximately 53,000 intentionally-set fires annually from 2003 to 2007, according to National Fire Protection Association figures. A disproportionate amount of these fires occur in spatio-temporal clusters, making them predictable and, perhaps, preventable. The objective of this research is to evaluate how the aggregation of data across space and target types (residential, non-residential, vehicle, outdoor and other) affects daily Arson forecast accuracy for several target types of Arson, and the ability to leverage information quantifying the autoregressive nature of intentional firesetting. To do this, we estimate, for the city of Detroit, Michigan, competing statistical models that differ in their ability to recognize potential temporal autoregressivity in the daily count of Arson fires. Spatial units vary from Census tracts, police precincts, to citywide. We find that (1) the out-of-sample performance of prospective hotspot models for Arson cannot usefully exploit the autoregressive properties of Arson at fine spatial scales, even though autoregression is significant in-sample, hinting at a possible bias-variance tradeoff; (2) aggregation of Arson across reported targets can yield a model that differs from by-target models; (3) spatial aggregation of data tends to increase forecast accuracy of Arson due partly to the ability to account for temporally dynamic firesetting; and (4) Arson forecast models that recognize temporal autoregression can be used to forecast daily Arson fire activity at the Citywide scale in Detroit. These results suggest a tradeoff between the collection of high resolution spatial data and the use of more sophisticated modeling techniques that explicitly account for temporal correlation.
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time to burn modeling wildland Arson as an autoregressive crime function
American Journal of Agricultural Economics, 2005Co-Authors: Jeffrey P Prestemon, David T ButryAbstract:Six Poisson autoregressive models of order p [PAR(p)] of daily wildland Arson ignition counts are estimated for five locations in Florida (1994‐2001). In addition, a fixed effects time-series Poisson model of annual Arson counts is estimated for all Florida counties (1995‐2001). PAR(p) model estimates reveal highly significant Arson ignition autocorrelation, lasting up to eleven days, in addition to seasonality and links to law enforcement, wildland management, historical fire, and weather. The annual fixed effects model replicates many findings of the daily models but also detects the influence of wages and poverty on Arson, in ways expected from theory. All findings support an economic model of crime.
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spatio temporal wildland Arson crime functions
Research Papers in Economics, 2005Co-Authors: David T Butry, Jeffrey P PrestemonAbstract:Wildland Arson creates damages to structures and timber and affects the health and safety of people living in rural and wildland urban interface areas. We develop a model that incorporates temporal autocorrelations and spatial correlations in wildland Arson ignitions in Florida. A Poisson autoregressive model of order p, or PAR(p) model, is estimated for six high Arson Census tracts in the state for the period 1994-2001. Spatio-temporal lags of wildland Arson ignitions are introduced as dummy variables indicating the presence of an ignition in previous days in surrounding Census tracts and counties. Temporal lags of ignition activity within the Census tract are shown to be statistically significant and larger than previously reported for non-spatial variants of the PAR(p) model. Spatio-temporal lagged relationships with current Arson that were statistically significant show that Arson activity up to a county away explains Arson patterns, and spatio-temporal lags longer than two days were not significant. Other variables showing significance include weather and wildfire activity in the previous six years, but prescribed fire and several variables that provide evidence that such activity is consistent with an economic model of crime were less commonly significant.
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spatio temporal wildland Arson crime functions
Selected paper presented at the American Agricultural Economics Association Annual Meeting Providence Rhode Island July 24-27 2005: American Agricultu, 2005Co-Authors: David T Butry, Jeffrey P PrestemonAbstract:Wildland Arson creates damages to structures and timber and affects the health and safety of people living in rural and wildland urban interface areas. We develop a model that incorporates temporal autocorrelations and spatial correlations in wildland Arson ignitions in Florida. A Poisson autoregressive model of order p, or PAR(p) model, is estimated for six high Arson Census tracts in the state for the period 1994-2001. Spatio-temporal lags of wildland Arson ignitions are introduced as dummy variables indicating the presence of an ignition in previous days in surrounding Census tracts and counties. Temporal lags of ignition activity within the Census tract are shown to be statistically significant and larger than previously reported for non-spatial variants of the PAR(p) model. Spatio-temporal lagged relationships with current Arson that are statistically significant show that Arson activity up to a county away explains Arson patterns, and spatio-temporal lags longer than two days were not significant. Other variables showing significance include weather and wildfire activity in the previous six years, but prescribed fire and several variables that provide evidence that such activity is consistent with an economic model of crime were less commonly significant.
Ray W. Cooksey - One of the best experts on this subject based on the ideXlab platform.
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International Journal of Offender Therapy and Comparative Criminology Psychological Profiling of Serial Arson Criminal Psychological Profiling of Serial Arson Crimes
2015Co-Authors: Richard N. Kocsis, Ray W. CookseyAbstract:Abstract: The practice of criminal psychological profiling is frequently cited as being appli-cable to serial Arson crimes. Despite this claim, there does not appear to be any empirical research that examines serial Arson offence behaviors in the context of profiling. This study seeks to develop an empirical model of serial Arsonist behaviors that can be systematically associated with probable offender characteristics. Analysis has produced a model of offence behaviors that identify four discrete behavior patterns, all of which share a constellation of common nondiscriminatory behaviors. The inherent behavioral themes of each of these pat-terns are exploredwith discussion of their broader implications for our understanding of serial Arson and directions for future research. Criminal psychological profiling is the forensic technique of analyzing crime behaviors to construct a descriptive template of probable offenders (Wilson, Lin-coln, & Kocsis, 1997). The practice of and research into profiling has predomi-nantly been focussed on crimes of sexual violence such as murder and rape. Although comparatively little research has actually been developed, profiling is nonetheless frequently cited as also being applicable to the investigation of Arson crimes (Holmes & Holmes, 1996; Rossmo, 1997; Vorpagel, 1982). Despite this reputation and acceptance of profiling by the law enforcement community, there exists a surprising dearth of rigorous empirical research on the topic of profiling (Kocsis, in press; Kocsis, Hayes & Irwin, 2002; Kocsis, Irwin, Hayes, & Nunn, 2000; Oleson, 1996). The objective of this study is to develop an empirical model for the criminal psychological profiling of serial Arson offences. The majority of current social science research on Arson is dominated by psy-chiatric or psychological studies that examine issues of mental status and/o
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criminal psychological profiling of serial Arson crimes
International Journal of Offender Therapy and Comparative Criminology, 2002Co-Authors: Richard N. Kocsis, Ray W. CookseyAbstract:The practice of criminal psychological profiling is frequently cited as being applicable to serial Arson crimes. Despite this claim, there does not appear to be any empirical research that examines serial Arson offence behaviors in the context of profiling. This study seeks to develop an empirical model of serial Arsonist behaviors that can be systematically associated with probable offender characteristics. Analysis has produced a model of offence behaviors that identify four discrete behavior patterns, all of which share a constellation of common nondiscriminatory behaviors. The inherent behavioral themes of each of these patterns are explored with discussion of their broader implications for our understanding of serial Arson and directions for future research.
Douglas S Thomas - One of the best experts on this subject based on the ideXlab platform.
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exploiting autoregressive properties to develop prospective urban Arson forecasts by target
Applied Geography, 2013Co-Authors: Jeffrey P Prestemon, David T Butry, Douglas S ThomasAbstract:Abstract Municipal fire departments responded to approximately 53,000 intentionally-set fires annually from 2003 to 2007, according to National Fire Protection Association figures. A disproportionate amount of these fires occur in spatio-temporal clusters, making them predictable and, perhaps, preventable. The objective of this research is to evaluate how the aggregation of data across space and target types (residential, non-residential, vehicle, outdoor and other) affects daily Arson forecast accuracy for several target types of Arson, and the ability to leverage information quantifying the autoregressive nature of intentional firesetting. To do this, we estimate, for the city of Detroit, Michigan, competing statistical models that differ in their ability to recognize potential temporal autoregressivity in the daily count of Arson fires. Spatial units vary from Census tracts, police precincts, to citywide. We find that (1) the out-of-sample performance of prospective hotspot models for Arson cannot usefully exploit the autoregressive properties of Arson at fine spatial scales, even though autoregression is significant in-sample, hinting at a possible bias-variance tradeoff; (2) aggregation of Arson across reported targets can yield a model that differs from by-target models; (3) spatial aggregation of data tends to increase forecast accuracy of Arson due partly to the ability to account for temporally dynamic firesetting; and (4) Arson forecast models that recognize temporal autoregression can be used to forecast daily Arson fire activity at the Citywide scale in Detroit. These results suggest a tradeoff between the collection of high resolution spatial data and the use of more sophisticated modeling techniques that explicitly account for temporal correlation.
Katarina Fritzon - One of the best experts on this subject based on the ideXlab platform.
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examining the role of similarity coefficients and the value of behavioural themes in attempts to link serial Arson offences
Journal of Investigative Psychology and Offender Profiling, 2013Co-Authors: Holly Ellingwood, Rebecca Mugford, Craig Bennell, Tamara Melnyk, Katarina FritzonAbstract:When relying on crime scene behaviours to link serial crimes, linking accuracy may be influenced by the measure used to assess across-crime similarity and the types of behaviours included in the analysis. To examine these issues, the present study compared the level of linking accuracy achieved by using the simple matching index (S) to that of the commonly used Jaccard's coefficient (J) across themes of Arson behaviour. The data consisted of 42 crime scene behaviours, separated into three behavioural themes, which were exhibited by 37 offenders across 114 solved Arsons. The results of logistic regression and receiver operating characteristic analysis indicate that, with the exception of one theme where S was more effective than J at discriminating between linked and unlinked crimes, no significant differences emerged between the two similarity measures. In addition, our results suggest that thematically unrelated behaviours can be used to link crimes with the same degree of accuracy as thematically related behaviours, potentially calling into the question the importance of theme-based approaches to behavioural linkage analysis. Copyright © 2012 John Wiley & Sons, Ltd.
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risk factors for recidivistic Arson in adult offenders
Psychiatry Psychology and Law, 2011Co-Authors: Rebekah Doley, Katarina Fritzon, Kenneth R Fineman, Mairead Dolan, Troy E McewanAbstract:This article reviews the current literature on known risk factors for recidivistic Arson, with a particular focus on factors that could be used to differentiate serial from “one-off” Arson offenders. The relevance of risk factors for general reoffending to recidivistic Arson is discussed, including the role of criminal history, mental illness, and sociodemographic factors. The specific roles of offence-related affect, cognitions, and the offender's interest in fire are considered, with recommendations for how theories from other areas of forensic psychology, such as the sex offender assessment and treatment literature, might be applied to the issue of deliberate fire-setting. Finally, protective factors are briefly discussed and the need for a structured risk assessment tool for deliberate firsetters is canvassed. Given that research into risk and recidivism in fire-setting is underdeveloped, suggestions are made throughout the review for the focus of future research into risk factors for serial Arson.
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Linking Arson incidents on the basis of crime scene behavior
Journal of Police and Criminal Psychology, 2004Co-Authors: Pekka Santtila, Katarina Fritzon, Anna Lena TamelanderAbstract:The present study investigated the possibility of statistically linking Arson cases based on consistency of behaviors from one crime scente to another. Serial and spree Arson cases were studied to differentiate underlying themes and to link cases committed by the same offender. The material consisted of 248 Arson cases which formed 42 series of Arsons. A content analysis using 45 dichotomous variables was carried out and principal compnents (PCA) analysis was performed to identify underlying themes. Summary scores reflecting the themes were calculated. Linking effectiveness was tested with a discriminant analysis using the summary scores. The PCA analysis was successful and underlying themes which were in accordance with previous studies could be identified. Six factors were retained, in the PCA. The linking of the Arson cases was possible to a satisfactory level: 33% of the cases could be correctly linked and for over 50% of the cases, the series they actually belonged to was among the ten series identified as most probable on the basis of the linking analysis. From a practical point of view, the results could be used as a basis for developing support systems for police investigations of Arson.
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the application of an action system model to destructive behaviour the examples of Arson and terrorism
Behavioral Sciences & The Law, 2001Co-Authors: Katarina Fritzon, David V Canter, Zoe WiltonAbstract:This article argues that criminal and deviant behaviour can be productively viewed through an action system framework. The idea is developed by considering two forms of destructive behaviour: Arson and barricade–hostage terrorist incidents. Two studies are presented. The first study tests the hypothesis that different forms of Arson will reflect the four dominant states that an action system can take; integrative, expressive, conservative, and adaptive. A smallest space analysis was performed on 46 variables describing 230 cases of Arson and the results identified the four themes of action system functioning. An examination of the personal characteristics of the Arsonists also produced four variable groupings and a combined analysis of the four action scales and four characteristics scales also supported the structural hypothesis of the action system model. The second study applied the action system model to the study acts of terrorist barricade–hostage incidents. A smallest space analysis of 44 variables coded from 41 incidents again revealed four distinct forms of activity, which were psychologically similar to the four modes of Arson identified in study one. Overall, these two studies provide support for the appropriateness of the action system framework as a way of classifying different forms of deviant behaviour. Copyright © 2001 John Wiley & Sons, Ltd.