Klemens, Ben
Overview
Works:  12 works in 84 publications in 4 languages and 3,217 library holdings 

Roles:  Author 
Classifications:  K1519.C6, 
Publication Timeline
.
Most widely held works by
Ben Klemens
Math you can't use : patents, copyright, and software by
Ben Klemens(
Book
)
13 editions published in 2006 in English and German and held by 481 WorldCat member libraries worldwide
"Gathering persepectives from law, computer science, mathematics, and economics, examines the intellectual property issues surrounding computer software and suggests how patents might accommodate the unique structure of code and copyright for software could be more effectively implemented"Provided by publisher
13 editions published in 2006 in English and German and held by 481 WorldCat member libraries worldwide
"Gathering persepectives from law, computer science, mathematics, and economics, examines the intellectual property issues surrounding computer software and suggests how patents might accommodate the unique structure of code and copyright for software could be more effectively implemented"Provided by publisher
21st century C by
Ben Klemens(
Book
)
42 editions published between 2012 and 2015 in 3 languages and held by 285 WorldCat member libraries worldwide
Throw out your old ideas about C and get to know a programming language that's substantially outgrown its origins. With this revised edition of 21st Century C, you'll discover uptodate techniques missing from other C tutorials, whether you're new to the language or just getting reacquainted. C isn't just the foundation of modern programming languages; it is a modern language, ideal for writing efficient, stateoftheart applications. Get past idioms that made sense on mainframes and learn the tools you need to work with this evolved and aggressively simple language. No matter what program
42 editions published between 2012 and 2015 in 3 languages and held by 285 WorldCat member libraries worldwide
Throw out your old ideas about C and get to know a programming language that's substantially outgrown its origins. With this revised edition of 21st Century C, you'll discover uptodate techniques missing from other C tutorials, whether you're new to the language or just getting reacquainted. C isn't just the foundation of modern programming languages; it is a modern language, ideal for writing efficient, stateoftheart applications. Get past idioms that made sense on mainframes and learn the tools you need to work with this evolved and aggressively simple language. No matter what program
Modeling with data : tools and techniques for scientific computing by
Ben Klemens(
Book
)
17 editions published between 2008 and 2009 in English and Undetermined and held by 245 WorldCat member libraries worldwide
'Modeling with Data' explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results
17 editions published between 2008 and 2009 in English and Undetermined and held by 245 WorldCat member libraries worldwide
'Modeling with Data' explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results
Information aggregation, with application to monotone ordering, advocacy, and conviviality by
Ben Klemens(
Book
)
3 editions published in 2003 in English and held by 7 WorldCat member libraries worldwide
Chapter 1 presents a convenient notation for describing methods of aggregating information to form posterior distributions, allowing a description of Bayesian updating and many of the cognitive errors people commit in the lab. Chapter 2 looks at the monotone ordering problem: if the prior distributions are ordered in some manner, what updating operations will preserve that ordering? Bayesian updating is a member of a small class of operators which preserve the monotone likelihood ratio property, but is not in the class of functions which preserve firstorder stochastic dominance. It also considers ordering distributions by their medians, which is useful for Political Science and other decision making applications
3 editions published in 2003 in English and held by 7 WorldCat member libraries worldwide
Chapter 1 presents a convenient notation for describing methods of aggregating information to form posterior distributions, allowing a description of Bayesian updating and many of the cognitive errors people commit in the lab. Chapter 2 looks at the monotone ordering problem: if the prior distributions are ordered in some manner, what updating operations will preserve that ordering? Bayesian updating is a member of a small class of operators which preserve the monotone likelihood ratio property, but is not in the class of functions which preserve firstorder stochastic dominance. It also considers ordering distributions by their medians, which is useful for Political Science and other decision making applications
C cheng xu she ji xin si wei by
Ben Klemens(
Book
)
1 edition published in 2015 in Chinese and held by 1 WorldCat member library worldwide
1 edition published in 2015 in Chinese and held by 1 WorldCat member library worldwide
Modeling with data : tools and techniques for scietifioc computing by
Ben Klemens(
Book
)
1 edition published in 2009 in English and held by 1 WorldCat member library worldwide
1 edition published in 2009 in English and held by 1 WorldCat member library worldwide
Information aggregation, with application to monotone ordering, advocacy, and conviviality by
Ben Klemens(
)
1 edition published in 2003 in Undetermined and held by 1 WorldCat member library worldwide
I. Chapter 1 presents a convenient notation for describing methods of aggregating information to form posterior distributions, allowing a description of Bayesian updating and many of the cognitive errors people commit in the lab. Chapter 2 looks at the monotone ordering problem: if the prior distributions are ordered in some manner, what updating operations will preserve that ordering? Bayesian updating is a member of a small class of operators which preserve the monotone likelihood ratio property, but is not in the class of functions which preserve firstorder stochastic dominance. It also considers ordering distributions by their medians, which is useful for Political Science and other decisionmaking applications. II. Chapter 3 presents a literature review of existing models of information aggregation from one party, and gives the very weak conditions under which one or two biased advocates will always reveal full information. Chapter 4 then presents a model of a trial, in which events are grouped into causal stories. Each story may point to a specific verdict, but the judge has leeway in selecting a verdict when multiple stories are shown to simultaneously be sufficient to explain an event. Two judges may be `perfect Bayesians', share the same priors, and still arrive at different verdicts for the same trial. Unlike the information revelation literature to date, there may be apropos stories and facts that neither party will want to reveal in equilibrium. III. Chapter 5 presents a simultaneous model of goods or actions which demonstrate conformity effects. Previous models of such goods universally describe people as acting in sequence; actors in the model here act simultaneously, so they must decide what to do based only on prior information about the distribution of tastes in the society. The shape of this distribution (e.g., centered around zero, skewed upward, or fattailed) predicts the number of people who will act in some systematic ways, which I catalog her
1 edition published in 2003 in Undetermined and held by 1 WorldCat member library worldwide
I. Chapter 1 presents a convenient notation for describing methods of aggregating information to form posterior distributions, allowing a description of Bayesian updating and many of the cognitive errors people commit in the lab. Chapter 2 looks at the monotone ordering problem: if the prior distributions are ordered in some manner, what updating operations will preserve that ordering? Bayesian updating is a member of a small class of operators which preserve the monotone likelihood ratio property, but is not in the class of functions which preserve firstorder stochastic dominance. It also considers ordering distributions by their medians, which is useful for Political Science and other decisionmaking applications. II. Chapter 3 presents a literature review of existing models of information aggregation from one party, and gives the very weak conditions under which one or two biased advocates will always reveal full information. Chapter 4 then presents a model of a trial, in which events are grouped into causal stories. Each story may point to a specific verdict, but the judge has leeway in selecting a verdict when multiple stories are shown to simultaneously be sufficient to explain an event. Two judges may be `perfect Bayesians', share the same priors, and still arrive at different verdicts for the same trial. Unlike the information revelation literature to date, there may be apropos stories and facts that neither party will want to reveal in equilibrium. III. Chapter 5 presents a simultaneous model of goods or actions which demonstrate conformity effects. Previous models of such goods universally describe people as acting in sequence; actors in the model here act simultaneously, so they must decide what to do based only on prior information about the distribution of tastes in the society. The shape of this distribution (e.g., centered around zero, skewed upward, or fattailed) predicts the number of people who will act in some systematic ways, which I catalog her
MA+H you can't use : patents, copyright, and software by
Ben Klemens(
Book
)
1 edition published in 2006 in Dutch and held by 1 WorldCat member library worldwide
1 edition published in 2006 in Dutch and held by 1 WorldCat member library worldwide
Estimating local poverty measures using satellite images a pilot application to Central America by
Ben Klemens(
)
2 editions published in 2015 in English and held by 1 WorldCat member library worldwide
Several studies have used satellite measures of human activity to complement measures of economic production. This paper builds on those studies by considering satellite measures for improving poverty measures. The paper uses localscale census and survey data from Guatemala to test at how fine a scale satellite measures are useful. Results show that supplementing survey data with satellite data leads to improvements in the estimates
2 editions published in 2015 in English and held by 1 WorldCat member library worldwide
Several studies have used satellite measures of human activity to complement measures of economic production. This paper builds on those studies by considering satellite measures for improving poverty measures. The paper uses localscale census and survey data from Guatemala to test at how fine a scale satellite measures are useful. Results show that supplementing survey data with satellite data leads to improvements in the estimates
C im 21 by
Ben Klemens(
)
1 edition published in 2013 in German and held by 0 WorldCat member libraries worldwide
1 edition published in 2013 in German and held by 0 WorldCat member libraries worldwide
Empirical performance of a decentralized civil violence model(
)
1 edition published in 2010 in English and held by 0 WorldCat member libraries worldwide
This paper provides an empirical examination of three potential drivers of decentralized rebellion: hardship, regime legitimacy, and repressive capacity. These are drawn from Epstein's (1) theoretical agentbased computational model published in this journal in 2002. Here, we develop a parsimonious threevariable probit model and test its statistical power against incidence data of decentralized rebellion drawn from the Political Instability Task Force dataset. We find the model's explanatory power to be high, with the signs predicted in the theoretical model supported at high significance. The results are found to be robust across a variety of statistical instruments for the theoretical independent variables. Epistemologically, this article also demonstrates the value of theorydriven econometrics
1 edition published in 2010 in English and held by 0 WorldCat member libraries worldwide
This paper provides an empirical examination of three potential drivers of decentralized rebellion: hardship, regime legitimacy, and repressive capacity. These are drawn from Epstein's (1) theoretical agentbased computational model published in this journal in 2002. Here, we develop a parsimonious threevariable probit model and test its statistical power against incidence data of decentralized rebellion drawn from the Political Instability Task Force dataset. We find the model's explanatory power to be high, with the signs predicted in the theoretical model supported at high significance. The results are found to be robust across a variety of statistical instruments for the theoretical independent variables. Epistemologically, this article also demonstrates the value of theorydriven econometrics
Finding optimal agentbased models by
Ben Klemens(
)
1 edition published in 2007 in English and held by 0 WorldCat member libraries worldwide
"This paper applies standard maximum likelihood (ML) techniques to find an optimal agentbased model (ABM), where optimal could refer to replicating a pattern or matching observed data. Because ML techniques produce a covariance matrix for the parameter estimates, the method here provides a means of determining to which parameters and conditions the ABM is sensitive, and which have limited effect on the outcome. Because the search method and the space of models searched is explicitly specified, the derivation of the final ABM is transparent and replicable. Hypotheses regarding parameters can be tested using standard likelihood ratio methods."
1 edition published in 2007 in English and held by 0 WorldCat member libraries worldwide
"This paper applies standard maximum likelihood (ML) techniques to find an optimal agentbased model (ABM), where optimal could refer to replicating a pattern or matching observed data. Because ML techniques produce a covariance matrix for the parameter estimates, the method here provides a means of determining to which parameters and conditions the ABM is sensitive, and which have limited effect on the outcome. Because the search method and the space of models searched is explicitly specified, the derivation of the final ABM is transparent and replicable. Hypotheses regarding parameters can be tested using standard likelihood ratio methods."
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Related Identities
 Coppola, Andrea
 World Bank Macroeconomics and Fiscal Management Global Practice Group
 Shron, Max
 Montgomery, Karen
 Shelby, Nicole Editor
 Roumeliotis, Rachel Editor
 MacDonald, Allyson Editor
 California Institute of Technology Division of Humanities and Social Sciences
 Jackson, Matthew O. Thesis advisor
 Brookings Institution Center on Social and Economic Dynamics
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Associated Subjects
Application softwareDevelopment Bayesian statistical decision theory C (Computer program language) Computer softwareLaw and legislation Decision makingMathematical models Economic development Geographic information systems Guatemala Intellectual property Intelligent agents (Computer software) Mathematical models Mathematical statistics Parameter estimation PovertyStatistical methods Remotesensing images Social conflictMathematical models United States