The Justification of Probability Measures in Statistical Mechanics*
... Precisely what sort of maneuvers are needed is a subject of some dispute. Even once such maneuvers are made, however, many accounts leave us having to say that the universe began its life in an exceedingly improbable state. We are then left wondering whether and how we are to explain this initial st ...
... Precisely what sort of maneuvers are needed is a subject of some dispute. Even once such maneuvers are made, however, many accounts leave us having to say that the universe began its life in an exceedingly improbable state. We are then left wondering whether and how we are to explain this initial st ...
Slides 17: Waiting for Disaster (PDF, 135 KB)
... associated terminology is grim. We will use it to model how long companies have to live, so for us the terminology fits. ...
... associated terminology is grim. We will use it to model how long companies have to live, so for us the terminology fits. ...
PDF
... classifiers with small error probability. One can, however, do even better than to derive classifiers from good regression estimators. One of the goals of this paper is to investigate consistency properties of an RBF-estimate of m and of the classifier derived from it, and of an RBF classifier based ...
... classifiers with small error probability. One can, however, do even better than to derive classifiers from good regression estimators. One of the goals of this paper is to investigate consistency properties of an RBF-estimate of m and of the classifier derived from it, and of an RBF classifier based ...
6.02 Lecture 9: Transmitting on a physical channel
... allows us to apply an important result from probability and statistics, called the cen tral limit theorem. This states that the sum of independent random variables is well approximated (under rather mild conditions) by a Gaussian random variable, with the approximation improving as more variables a ...
... allows us to apply an important result from probability and statistics, called the cen tral limit theorem. This states that the sum of independent random variables is well approximated (under rather mild conditions) by a Gaussian random variable, with the approximation improving as more variables a ...
A History and Introduction to the Algebra of Conditional Events and
... the estimation of an unknown parameter of a model, knowledge is probabilistic in nature, namely the prior distribution of that parameter (if you are Bayesian), and the observations of the random variable of interest. The logic need not be spelled out since it is always the classical two-valued one. ...
... the estimation of an unknown parameter of a model, knowledge is probabilistic in nature, namely the prior distribution of that parameter (if you are Bayesian), and the observations of the random variable of interest. The logic need not be spelled out since it is always the classical two-valued one. ...
Public-key Cryptosystems Provably Secure against Chosen
... hnplementations of the notion were suggested by Rivest, Shamir and Adleman [28] and Merkle and Hellman [22]. The exact nature of security of these implementations was not given in a precise form, since an exact definition of security was not known at the time. Rabin [26], nevertheless, has given a s ...
... hnplementations of the notion were suggested by Rivest, Shamir and Adleman [28] and Merkle and Hellman [22]. The exact nature of security of these implementations was not given in a precise form, since an exact definition of security was not known at the time. Rabin [26], nevertheless, has given a s ...
Detachment, Probability, and Maximum Likelihood
... coming up heads when tossed is some fixed number, although one does not know exactly what the number is. The problem is to estimate the statistical probability after observing the outcome of several tosses o f the coin. Notice that such estimation is n o t the inference that the statistical probabil ...
... coming up heads when tossed is some fixed number, although one does not know exactly what the number is. The problem is to estimate the statistical probability after observing the outcome of several tosses o f the coin. Notice that such estimation is n o t the inference that the statistical probabil ...
Research on Financial Early Warning
... countable set T call the parameter space. The possible values of X(t) form a countable set S call the state space. The process of random can be divided into four kinds according to whether S and T are discrete aggregate or not. Markov is only refer part of it in the process of random. We often call ...
... countable set T call the parameter space. The possible values of X(t) form a countable set S call the state space. The process of random can be divided into four kinds according to whether S and T are discrete aggregate or not. Markov is only refer part of it in the process of random. We often call ...
Innovation, growth and aggregate volatility from a
... the economy grows by innovations. These are stochastic events of two types: the first type is a productivity rise in an existing sector, whereas the second type is the creation of a new sector of production. Given the economic problem at hand, we assume that the pace of innovations is regulated by a ...
... the economy grows by innovations. These are stochastic events of two types: the first type is a productivity rise in an existing sector, whereas the second type is the creation of a new sector of production. Given the economic problem at hand, we assume that the pace of innovations is regulated by a ...
Probability box
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A probability box (or p-box) is a characterization of an uncertain number consisting of both aleatoric and epistemic uncertainties that is often used in risk analysis or quantitative uncertainty modeling where numerical calculations must be performed. Probability bounds analysis is used to make arithmetic and logical calculations with p-boxes.An example p-box is shown in the figure at right for an uncertain number x consisting of a left (upper) bound and a right (lower) bound on the probability distribution for x. The bounds are coincident for values of x below 0 and above 24. The bounds may have almost any shapes, including step functions, so long as they are monotonically increasing and do not cross each other. A p-box is used to express simultaneously incertitude (epistemic uncertainty), which is represented by the breadth between the left and right edges of the p-box, and variability (aleatory uncertainty), which is represented by the overall slant of the p-box.