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This Tract presents an elaboration of the notion of 'contiguity', which is a concept of 'nearness' of sequences of probability measures. It provides a powerful mathematical tool for establishing certain theoretical results with applications in statistics, particularly in large sample theory problems, where it simplifies derivations and points the way to important results. The potential of this concept has so far only been touched upon in the existing literature, and this book provides the first systematic discussion of it. Alternative characterizations of contiguity are first described and related to more familiar mathematical ideas of a similar nature. A number of general theorems are formulated and proved. These results, which provide the means of obtaining asymptotic expansions and distributions of likelihood functions, are essential to the applications which follow.
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Nowadays, the information transfer speed (on the web, but not only) requires the predisposition of ever more adequate analysis tools for working with data and increasingly faster algorithms, in order to allow the so-called decision maker to make decision based on information which can become obsolete very quickly with time. In the current situation, analysing this information in order to simulate complex decision-making scenarios could prove fundamental to secure an advantage over competitors. This text introduces the true art of Statistical Computing. In other words, it illustrates how computer programming skills in the development of algorithms can be used within Statistics for the virtual simulation and replication of realities and experiments of varying complexity. In order to do so, it uses the excellent development environment "R".
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Nowadays, the information transfer speed (on the web, but not only) requires the predisposition of ever more adequate analysis tools for working with data and increasingly faster algorithms, in order to allow the so-called decision maker to make decision based on information which can become obsolete very quickly with time. In the current situation, analysing this information in order to simulate complex decision-making scenarios could prove fundamental to secure an advantage over competitors. This text introduces the true art of Statistical Computing. In other words, it illustrates how computer programming skills in the development of algorithms can be used within Statistics for the virtual simulation and replication of realities and experiments of varying complexity. In order to do so, it uses the excellent development environment "R".
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Statistical physics --- Probability measures --- Probability measures. --- Statistical physics.
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Nowadays, the information transfer speed (on the web, but not only) requires the predisposition of ever more adequate analysis tools for working with data and increasingly faster algorithms, in order to allow the so-called decision maker to make decision based on information which can become obsolete very quickly with time. In the current situation, analysing this information in order to simulate complex decision-making scenarios could prove fundamental to secure an advantage over competitors. This text introduces the true art of Statistical Computing. In other words, it illustrates how computer programming skills in the development of algorithms can be used within Statistics for the virtual simulation and replication of realities and experiments of varying complexity. In order to do so, it uses the excellent development environment "R".
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Nowadays, the information transfer speed (on the web, but not only) requires the predisposition of ever more adequate analysis tools for working with data and increasingly faster algorithms, in order to allow the so-called decision maker to make decision based on information which can become obsolete very quickly with time. In the current situation, analysing this information in order to simulate complex decision-making scenarios could prove fundamental to secure an advantage over competitors. This text introduces the true art of Statistical Computing. In other words, it illustrates how computer programming skills in the development of algorithms can be used within Statistics for the virtual simulation and replication of realities and experiments of varying complexity. In order to do so, it uses the excellent development environment "R".
Choose an application
Nowadays, the information transfer speed (on the web, but not only) requires the predisposition of ever more adequate analysis tools for working with data and increasingly faster algorithms, in order to allow the so-called decision maker to make decision based on information which can become obsolete very quickly with time. In the current situation, analysing this information in order to simulate complex decision-making scenarios could prove fundamental to secure an advantage over competitors. This text introduces the true art of Statistical Computing. In other words, it illustrates how computer programming skills in the development of algorithms can be used within Statistics for the virtual simulation and replication of realities and experiments of varying complexity. In order to do so, it uses the excellent development environment "R".
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