Books on the topic 'Transition probability'

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1

Geoffrey, Grimmett, North Atlantic Treaty Organization. Scientific Affairs Division., and NATO Advanced Study Institute on Probability Theory of Spatial Disorder and Phase Transition (1993 : Cambridge, England), eds. Probability and phase transition. Dordrecht: Kluwer Academic Publishers, 1994.

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2

Grimmett, Geoffrey, ed. Probability and Phase Transition. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-015-8326-8.

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3

Grimmett, Geoffrey. Probability and Phase Transition. Dordrecht: Springer Netherlands, 1994.

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4

Hawkins, D. L. Inference about the transition-point in NBUE-NWUE or NWUE-NBUE models. Arlington, Tex: Dept. of Mathematics, University of Texas at Arlington, 1990.

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5

Stochastic ordinary and stochastic partial differential equations: Transition from microscopic to macroscopic equations. New York: Springer Science+Business Media, 2008.

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6

Fokker-Planck-Kolmogorov equations. Providence, Rhode Island: American Mathematical Society, 2015.

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7

Michel, Pleimling, and SpringerLink (Online service), eds. Non-Equilibrium Phase Transitions: Volume 2: Ageing and Dynamical Scaling Far from Equilibrium. Dordrecht: Springer Science+Business Media B.V., 2010.

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8

1936-, Tawara H., ed. Atomic multielectron processes. Berlin: Springer, 1998.

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9

Barker, Jeffries Jay, Crosley David R. 1941-, and United States. National Aeronautics and Space Administration., eds. Transition probabilities in OH A²[sigma]⁺ - X²[pi]₁: bands with vʹ = 0 and 1, vʺ = 0 to 4. Menlo Park, Calif: Molecular Physics Dept., SRI International, 1986.

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10

National Aeronautics and Space Administration (NASA) Staff. Charge Exchange Transition Probability for Collisions Between Unlike Ions and Atoms Within the Adiabatic Approximation. Independently Published, 2018.

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11

Rau, Jochen. Introduction. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199595068.003.0001.

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Statistical mechanics concerns the transition from the microscopic to the macroscopic realm. On a macroscopic scale new phenomena arise that have no counterpart in the microscopic world. For example, macroscopic systems have a temperature; they might undergo phase transitions; and their dynamics may involve dissipation. How can such phenomena be explained? This chapter discusses the characteristic differences between the microscopic and macroscopic realms and lays out the basic challenge of statistical mechanics. It suggests how, in principle, this challenge can be tackled with the help of conservation laws and statistics. The chapter reviews some basic notions of classical probability theory. In particular, it discusses the law of large numbers and illustrates how, despite the indeterminacy of individual events, statistics can make highly accurate predictions about totals and averages.
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12

Levin, Frank S. The Hydrogen Atom and Its Colorful Photons. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198808275.003.0010.

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The energies, kets and wave functions obtained from the Schrödinger equation for the hydrogen atom are examined in Chapter 9. Three quantum numbers are identified. The energies turn out to be the same as in the Bohr model, and an energy-level diagram appropriate to the quantum description is constructed. Graphs of the probability distributions are interpreted as the electron being in a “cloud” around the proton, rather than at a fixed position: the atom is fuzzy, not sharp-edged. The wavelengths of the five photons of the Balmer series are shown to be in the visible range. These photons are emitted when electrons transition from higher-excited states to the second lowest one, which means that electronic-type transitions underlie the presence of colors in our visible environment. The non-collapse of the atom, required by classical physics, is shown to arise from the structure of Schrödinger’s equation.
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13

Gelman, Andrew, and Deborah Nolan. Statistical inference. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198785699.003.0009.

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This chapter begins with a very successful demonstration that illustrates many of the general principles of statistical inference, including estimation, bias, and the concept of the sampling distribution. Students each take a “random” sample of different size candies, weigh them, and estimate the total weight of all candies. Then various demonstrations and examples are presented that take the students on the transition from probability to hypothesis testing, confidence intervals, and more advanced concepts such as statistical power and multiple comparisons. These activities include use an inflatable globe, short-term memory test, first digits of street addresses, and simulated student IQs.
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14

Maurizio, Roxana, and Ana Paula Monsalvo. Informality, labour transitions, and the livelihoods of workers in Latin America. 19th ed. UNU-WIDER, 2021. http://dx.doi.org/10.35188/unu-wider/2021/953-2.

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This paper studies the incidence and heterogeneity of labour informality in six Latin American countries—Argentina, Brazil, Ecuador, Mexico, Paraguay, and Peru. We divide workers into five work statuses: formal wage-employed, formal self-employed, upper-tier informal wage-employed, lower-tier informal wage-employed, and informal self-employed. We evaluate the patterns of the occupational turnover between these work statuses and assess their impact on wage dynamics. In all the countries, wages are highest for formal workers and lowest for lower-tier informal jobs. The proportion of formal workers who maintain their work status of origin or move up the job ladder is significantly higher than those who transition into lower-paying work statuses. However, despite the high labour turnover experienced by lower-tier informal wage employees, most failed to move up the wage ladder. Education plays an important role, as it increases the probability of transitioning into a better job and, within informality, the chance of better wages.
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15

Bao, Yun, Carl Chiarella, and Boda Kang. Particle Filters for Markov-Switching Stochastic Volatility Models. Edited by Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.9.

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This chapter proposes an auxiliary particle filter algorithm for inference in regime switching stochastic volatility models in which the regime state is governed by a first-order Markov chain. It proposes an ongoing updated Dirichlet distribution to estimate the transition probabilities of the Markov chain in the auxiliary particle filter. A simulation-based algorithm is presented for the method that demonstrates the ability to estimate a class of models in which the probability that the system state transits from one regime to a different regime is relatively high. The methodology is implemented in order to analyze a real-time series, namely, the foreign exchange rate between the Australian dollar and the South Korean won.
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16

NonEquilibrium Phase Transitions Volume I Theoretical and Mathematical Physics. Springer, 2008.

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17

Salvucci, Vincenzo, and Finn Tarp. Estimating poverty transitions in Mozambique using synthetic panels: A validation exercise and an application to cross-sectional survey data. 26th ed. UNU-WIDER, 2021. http://dx.doi.org/10.35188/unu-wider/2021/964-8.

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In this paper we first validate the use of the synthetic panels technique in the context of the 2014/15 intra-year panel survey data for Mozambique, and then apply the same technique to the 1996/97, 2002/03, 2008/09, and 2014/15 cross-sectional household budget surveys for the same country. We find that in most analyses poverty rates and poverty transitions estimated using synthetic panels provide results that are close to the true values obtained using the 2014/15 panel data. With respect to intra-year poverty dynamics, we find that Mozambique has a high intra-year variability in consumption and poverty, and a very high degree of intra-year poverty immobility, with a big portion of the population remaining either in poverty or out of poverty over the whole year, with smaller percentages of individuals moving upward or downward. With respect to the 1996/97, 2002/03, 2008/09, and 2014/15 cross-sectional surveys, our results suggest that in most year-to-year comparisons there is a greater proportion of people getting out of poverty than falling into poverty, consistent with the poverty-reduction process observed, but the percentage of people staying in poverty over time appears to be substantially higher, involving about one-third of the population in most years. Further analyses on the 2008/09 and 2014/15 surveys estimate that for an individual who was in the vulnerable group in 2008/09, there is a 60 per cent probability of remaining in the same group, whereas the probability of becoming non-vulnerable is lower than the probability of entering poverty. This constitutes the first attempt to provide an insight into poverty dynamics in Mozambique using all the available survey data.
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18

Krylov, Nicolai V., Michael Rockner, Vladimir I. Bogachev, and Stanislav V. Shaposhnikov. Fokker-Planck-Kolmogorov Equations. American Mathematical Society, 2015.

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19

Slade, Gordon, and Martin T. Barlow. Random Graphs, Phase Transitions, and the Gaussian Free Field: PIMS-CRM Summer School in Probability, Vancouver, Canada, June 5-30, 2017. Springer, 2019.

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20

Slade, Gordon, and Martin T. Barlow. Random Graphs, Phase Transitions, and the Gaussian Free Field: PIMS-CRM Summer School in Probability, Vancouver, Canada, June 5–30, 2017. Springer, 2019.

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21

Slade, Gordon, and Martin T. Barlow. Random Graphs, Phase Transitions, and the Gaussian Free Field: PIMS-CRM Summer School in Probability, Vancouver, Canada, June 5-30 2017. Springer International Publishing AG, 2021.

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22

Shevelko, Viatcheslav, and Hiro Tawara. Atomic Multielectron Processes (Springer Series on Atomic, Optical, and Plasma Physics). Springer, 1999.

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23

Noordhof, Paul. A Variety of Causes. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780199251469.001.0001.

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Metaphysicians often focus on what is vertically fundamental, appealing to grounding or truth-making, rather than what is horizontally fundamental: what must be common to any metaphysical picture of the universe. There is a case for causation being one such feature. But how should it be characterized? A revised semantics for counterfactuals provides the basis for a new counterfactual analysis of causation that is compatible with Humean supervenience but also appropriate for a non-Humean metaphysical framework. Causes (independently of their competitors) both make the chance of an effect very much greater than its mean background chance in the circumstances and actually influences the probability of the effect in this way at the time at which the effect occurred via a complete causal chain. Causation understood in this way is a non-transitive relation. It is neutral over the metaphysics of causes and effects but allows a natural way for events to be understood as one fundamental type of causation, the other being property causation. Although negative causal statements are true, there are no cases of negative causation. The analysis explains how causation involving substantial processes is only one variety of causation, others include double prevention. It allows for a variety of micro- and macro-properties to be the basis of the difference between cause and effect. Laws are patterns of causation realized in different ways in different metaphysical pictures. The analysis of causation characterizes a horizontally fundamental property whose modal character depends upon its different realizations.
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24

The Random-Cluster Model (Grundlehren der mathematischen Wissenschaften). Springer, 2006.

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