are yet no limit theorems corresponding to more general step-wise or mixed processes withcontinuous time governed by integro-differential equations indicated above.6. The Logical Principles of the Theory of <strong>Probability</strong>From the viewpoint of justifying the theory it is natural to separate it into two parts. The first,elementary component is only concerned with patterns involving a finite number of events. The nonelementarypart begins when some r<strong>and</strong>om variable is assumed to be able to take an infinite numberof values (for example, when it is being strictly subject to the Gauss law) <strong>and</strong> extends up to the mostmodern constructions with distributions of probabilities in various functional spaces. It is evident inadvance that the entire second part connected with mathematical infinity cannot claim to have asimpler relation to reality than the mathematics of the infinite in general, i.e., than, for example, thetheory of irrational numbers or the differential calculus.6.1. The Logical Principles of the Elementary Theory of <strong>Probability</strong>. The events of any finitesystem can be compiled from a finite number of pairwise incompatible events. The matter is thereforecompletely reduced to1) Ascertaining the real sense of the following pattern: Under some conditions S one <strong>and</strong> only oneof the events A 1 , A 2 , …, A n necessarily occurs with each of them having, given these conditions,probability P(A i );2) Justifying that the pattern in Item 1) always leads toP(A i ) ≥ 0, P(A 1 ) + P(A 2 ) + … + P(A n ) = 1.This problem is known to be solved in different ways. Some believe that the determination of theprobabilities P(A i ) is only scientifically sensible if the conditions S can be repeated indefinitely manytimes <strong>and</strong> they substantiate, by some method, the concept of probability by the frequency of theoccurrence of the event. Other authors, however, consider that the concept of equiprobability (which,generally speaking, can be introduced without dem<strong>and</strong>ing an indefinite repetition of the conditions S)is primary <strong>and</strong> assume it as the base for defining the numerical value of probability. Both theseapproaches can be subjectively <strong>and</strong> idealistically colored; apparently, however, they can also beworked out from the viewpoint of objective materialism. The pertinent <strong>Soviet</strong> literature is scarce; inaddition to introductions in textbooks <strong>and</strong> popular literature, we only indicate Khinchin’s criticalpaper [13].6.2. The Substantiation of the Non-Elementary Chapters of the Theory of<strong>Probability</strong>. When retracting the finiteness of the system F = {A} of events to which definiteprobability {probabilities} P(A) is {are} assigned, it is natural to dem<strong>and</strong> that these events constitutea Boolean algebra with the probability being a non-negative function of its element equal to 1 for aunit of this algebra (Glivenko [6]). It is also possible to dem<strong>and</strong> that P(A) = 0 only for the zero of thealgebra (that is, for the one <strong>and</strong> only impossible event).The question about countable additivity of the probability does not arise here since for a Booleanalgebra a sum of a countable number of elements has no sense. It is natural, however, to define thesum A k , 1 ≤ k < ¦ , as an event A for whichlim P[( A k – A) (A – A k )] = 0 as n § ¦ .Then countable additivity will certainly take place.The Boolean algebra of events can be incomplete in the sense that a countable sum of its elementsdoes not always exist. Then, however, it can be replenished <strong>and</strong> this operation is uniquely defined. Itis as natural as the introduction of irrational numbers. On principle, Glivenko’s concept just describedis the most natural. However,1) The axiomatics of the theory of probability understood as the theory of complete normedBoolean algebras is rather complicated.2) In this theory, the definition of the concept of r<strong>and</strong>om variable is too complicated.
It is therefore necessary to make use of the main Boolean algebra as a Boolean algebra of the setsof elementary events. Such events can be introduced as ideals of the main algebra (Glivenko [6])which again leads to the Kolmogorov system (§3).The shortcoming of the transition to the set-theoretic concept with elementary events is that itinvariably leads to non-empty events having zero probability. That the sacrifice of one of the naturalprinciples of the elementary theory of probability is unavoidable is already seen in the simplestexamples of r<strong>and</strong>om variables with continuous distributions.Notes1. Our further exposition is centered around scientific problems rather than scientific schools.2. A singular distribution function describes a constant magnitude.3. The problem can be precisely posed in the following way: Under what conditions imposed onthe numbers c ij can we guarantee the validity of the relationP{lim [| n – E n |/n] = 0} = 1for the sums (1.3.1) of r<strong>and</strong>om variables n having second momentsc ij = E[( i – E i) ( j – E j)]?4. For the theory of probability, Borel’s countable additivity of probability was new here. On thejustification of this axiom see our last section. Right now, we only note that all the interestingconcrete results based on this axiom allow also a pre-limiting interpretation independent from it; seefor example Bernstein’s interpretation [41, pp. 155 – 156] of the strong law of large numbers.5. That is, from among those systems where any appeal to the obvious meaning of such notions asevent, incompatible events, event A is a corollary of event B, etc is ruled out.A6. {Later Gnedenko began calling the equality (4.2.1) the generalized Markov equation, see his# (Course in Theory of <strong>Probability</strong>). M., 1954, p. 387, <strong>and</strong> Lehrbuch derWahrscheinlichkeitsrechnung. Berlin, 1968, p. 28<strong>7.</strong>}<strong>7.</strong> Boiarsky [3] indicated their interesting two-dimensional analogue.8. N.V. Smirnov. Mathematical statistics: new directions.Vestnik Akademii Nauk SSSR, No. 7, vol. 31, 1961, pp. 53 – 58[Introduction] For a long time mathematical or variational statistics was understood as aspecial discipline that justified various methods of studying the biological phenomena ofvariability <strong>and</strong> heredity. This comparatively narrow range of problems constituted the mainsubject of researches of the British Biometric school headed by Karl Pearson. Soon, however,the methods that he had advanced found fruitful applications in a number of other fields, – inmeteorology, geophysics, hydrology, agronomy, animal science, forestry, in problems ofchecking <strong>and</strong> testing mass production, etc. Under the influence of the increasing dem<strong>and</strong>sthis discipline developed during the last decades in a considerably wider channel. At present,we already see a sufficiently shaped outline of a new branch of mathematics aiming atdeveloping rational methods of studying mass processes.For the last 30 years, the works of <strong>Soviet</strong> mathematicians were playing a sufficientlyimportant progressive part in developing mathematical statistics. The splendid achievementsof our mathematicians in the directly adjoining field of probability theory (of Kolmogorov, inaxiomatics <strong>and</strong> the theory of stochastic processes; of Bernstein, in limit theorems; ofKhinchin, et al) obviously influenced the progress in this science to a very considerableextent.The usual theoretical pattern (that does not, however, claim to be exhaustively general)with which various formulations of the problems in mathematical statistics are connected, isknown well enough. Here, the object of investigation is some system whose states are
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[3] I bear in mind the well-known p
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successes of physical statistics. B
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classes of independent facts whose
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distribution is a corollary of the
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examine in the first place the curv
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12. According to Bortkiewicz’ ter
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Khinchin, A.Ya. 43. Math. Ann. 101,
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7. DAN 115, 1957, 49 - 52.Pinsker,
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Anderson, T.W., Darling, D.A. (1952
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Statistical problems in radio engin
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observations for its power with reg
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securing against mistakes (A.N. Kry
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of the others, then its distributio
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In Kiev, in the 1930s, N.M. Krylov