5,325 research outputs found
From Models to Simulations
This book analyses the impact computerization has had on contemporary science and explains the origins, technical nature and epistemological consequences of the current decisive interplay between technology and science: an intertwining of formalism, computation, data acquisition, data and visualization and how these factors have led to the spread of simulation models since the 1950s.
Using historical, comparative and interpretative case studies from a range of disciplines, with a particular emphasis on the case of plant studies, the author shows how and why computers, data treatment devices and programming languages have occasioned a gradual but irresistible and massive shift from mathematical models to computer simulations
"Rotterdam econometrics": publications of the econometric institute 1956-2005
This paper contains a list of all publications over the period 1956-2005, as reported in the Rotterdam Econometric Institute Reprint series during 1957-2005.
Microsimulation as an Instrument to Evaluate Economic and Social Programmes
In recent years microsimulation models (MSMs) have been increasingly applied in quantitative analyses of the individual impacts of economic and social programme policies. The suitability of using microsimulation as an instrument to analyze main and side policy impacts at the individual level will be discussed in this paper by characterizing: the general approach and principles of the two general microsimulation approaches: static and dynamic (cross-section and lifecycle) microsimulation, the structure of MSMs with institutional regulations and behavioural response, panel data and behavioural change, deterministic and stochastic microsimulation, the 4M-strategy to combine microtheory, microdata, microestimation and microsimulation, and pinpointing applications and recent developments. To demonstrate the evaluation of economic and social programmes by microsimulation, two examples concerning a dynamic (cross-section and life-cycle) microsimulation of the German retirement pension reform and a combined static/dynamic microsimulation of the recent German tax reform with its behavioural impacts on formal and informal economic activities of private households are briefly described. Evaluating the evaluation of economic and social programmes with microsimulation models finally is followed by concluding remarks about some future developments.microsimulation, evaluation of economic and social-political programms
Microsimulation as an Instrument to Evaluate Economic and Social Programmes
In recent years microsimulation models (MSMs) have been increasingly applied in quantitative analyses of the individual impacts of economic and social programme policies. The suitability of using microsimulation as an instrument to analyze main and side policy impacts at the individual level will be discussed in this paper by characterizing: the general approach and principles of the two general microsimulation approaches: static and dynamic (cross-section and lifecycle) microsimulation, the structure of MSMs with institutional regulations and behavioural response, panel data and behavioural change, deterministic and stochastic microsimulation, the 4M-strategy to combine microtheory, microdata, microestimation and microsimulation, and pinpointing applications and recent developments. To demonstrate the evaluation of economic and social programmes by microsimulation, two examples concerning a dynamic (cross-section and life-cycle) microsimulation of the German retirement pension reform and a combined static/dynamic microsimulation of the recent German tax reform with its behavioural impacts on formal and informal economic activities of private households are briefly described. Evaluating the evaluation of economic and social programmes with microsimulation models finally is followed by concluding remarks about some future developments.microsimulation, evaluation of economic and social-political programms
Quantitative magnetic resonance image analysis via the EM algorithm with stochastic variation
Quantitative Magnetic Resonance Imaging (qMRI) provides researchers insight
into pathological and physiological alterations of living tissue, with the help
of which researchers hope to predict (local) therapeutic efficacy early and
determine optimal treatment schedule. However, the analysis of qMRI has been
limited to ad-hoc heuristic methods. Our research provides a powerful
statistical framework for image analysis and sheds light on future localized
adaptive treatment regimes tailored to the individual's response. We assume in
an imperfect world we only observe a blurred and noisy version of the
underlying pathological/physiological changes via qMRI, due to measurement
errors or unpredictable influences. We use a hidden Markov random field to
model the spatial dependence in the data and develop a maximum likelihood
approach via the Expectation--Maximization algorithm with stochastic variation.
An important improvement over previous work is the assessment of variability in
parameter estimation, which is the valid basis for statistical inference. More
importantly, we focus on the expected changes rather than image segmentation.
Our research has shown that the approach is powerful in both simulation studies
and on a real dataset, while quite robust in the presence of some model
assumption violations.Comment: Published in at http://dx.doi.org/10.1214/07-AOAS157 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Microsimulation - A Survey of Methods and Applications for Analyzing Economic and Social Policy
This essential dimensions of microsimulation as an instrument to analyze and forecast the individual impacts of alternative economic and social policy measures are surveyed in this study. The basic principles of microsimulation, which is a tool for practical policy advising as well as for research and teaching, are pointed out and the static and dynamic (cross-section and life-cycle) approaches are compared to one another. Present and past developments of microsimulation models and their areas of application are reviewed, focusing on the US, Europe and Australia. Based on general requirements and components of microsimulation models a microsimulation model's actual working mechanism are discussed by a concrete example: the concept and realization of MICSIM, a PC microsimulation model based on a relational database system, an offspring of the Sfb 3 Statitic Microsimulation Model. Common issues of microsimulation modeling are regarded: micro/macro link, behavioural response and the important question of evaluating microsimulation results. The concluding remarks accentuate the increasing use of microcomputers for microsimulation models also for teaching purposes.Microsimulation, Microanalytic Simulation Models, Microanalysis, Economic and Social Policy Analysis
Phenotypic evolution studied by layered stochastic differential equations
Time series of cell size evolution in unicellular marine algae (division
Haptophyta; Coccolithus lineage), covering 57 million years, are studied by a
system of linear stochastic differential equations of hierarchical structure.
The data consists of size measurements of fossilized calcite platelets
(coccoliths) that cover the living cell, found in deep-sea sediment cores from
six sites in the world oceans and dated to irregular points in time. To
accommodate biological theory of populations tracking their fitness optima, and
to allow potentially interpretable correlations in time and space, the model
framework allows for an upper layer of partially observed site-specific
population means, a layer of site-specific theoretical fitness optima and a
bottom layer representing environmental and ecological processes. While the
modeled process has many components, it is Gaussian and analytically tractable.
A total of 710 model specifications within this framework are compared and
inference is drawn with respect to model structure, evolutionary speed and the
effect of global temperature.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS559 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Nonparametric inference of doubly stochastic Poisson process data via the kernel method
Doubly stochastic Poisson processes, also known as the Cox processes,
frequently occur in various scientific fields. In this article, motivated
primarily by analyzing Cox process data in biophysics, we propose a
nonparametric kernel-based inference method. We conduct a detailed study,
including an asymptotic analysis, of the proposed method, and provide
guidelines for its practical use, introducing a fast and stable regression
method for bandwidth selection. We apply our method to real photon arrival data
from recent single-molecule biophysical experiments, investigating proteins'
conformational dynamics. Our result shows that conformational fluctuation is
widely present in protein systems, and that the fluctuation covers a broad
range of time scales, highlighting the dynamic and complex nature of proteins'
structure.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS352 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Bayesian inference and model choice in a hidden stochastic two-compartment model of hematopoietic stem cell fate decisions
Despite rapid advances in experimental cell biology, the in vivo behavior of
hematopoietic stem cells (HSC) cannot be directly observed and measured.
Previously we modeled feline hematopoiesis using a two-compartment hidden
Markov process that had birth and emigration events in the first compartment.
Here we perform Bayesian statistical inference on models which contain two
additional events in the first compartment in order to determine if HSC fate
decisions are linked to cell division or occur independently. Pareto Optimal
Model Assessment approach is used to cross check the estimates from Bayesian
inference. Our results show that HSC must divide symmetrically (i.e., produce
two HSC daughter cells) in order to maintain hematopoiesis. We then demonstrate
that the augmented model that adds asymmetric division events provides a better
fit to the competitive transplantation data, and we thus provide evidence that
HSC fate determination in vivo occurs both in association with cell division
and at a separate point in time. Last we show that assuming each cat has a
unique set of parameters leads to either a significant decrease or a
nonsignificant increase in model fit, suggesting that the kinetic parameters
for HSC are not unique attributes of individual animals, but shared within a
species.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS269 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
- …