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1

An introduction to measure-theoretic probability. Boston: Elsevier Academic Press, 2005.

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2

David, Pollard. A user's guide to measure theoretic probability. Cambridge: Cambridge University Press, 2002.

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3

Asmussen, Søren. Measure-theoretic foundations of probability theory in Polish spaces. 2nd ed. Copenhagen, Denmark: Institute of Mathematical Statistics, University of Copenhagen, 1987.

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4

Gallant, A. Ronald. An introduction to econometric theory: Measure-theoretic probability and statistics with applications to economics. Princeton, N.J: Princeton University Press, 1997.

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5

Fremlin, David Heaver. Set-theoretic measure theory. Colchester: Torres Fremlin, 2008.

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6

Fremlin, D. H. Set-theoretic measure theory. Colchester: Torres Fremlin, 2008.

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7

Adams, Malcolm Ritchie. Measure theory and probability. Monterey, Calif: Wadsworth & Brooks/Cole Advanced Books and Software, 1986.

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8

1937-, Guillemin V., ed. Measure Theory and Probability. Boston, USA: Birkhäuser, 1996.

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9

Ash, Robert B. Probability and measure theory. 2nd ed. San Diego: Harcourt/Academic Press, 2000.

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10

Adams, Malcolm, and Victor Guillemin. Measure Theory and Probability. Boston, MA: Birkhäuser Boston, 1996. http://dx.doi.org/10.1007/978-1-4612-0779-5.

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11

Probability and Measure. 3rd ed. New York, USA: Wiley-Interscience, 1995.

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12

Probability and measure. 2nd ed. New York: Wiley, 1986.

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13

Probability and measure. Hoboken, N.J: Wiley, 2012.

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14

Pitt, H. R. Integration, measure, and probability. Mineola, N.Y: Dover Publications, Inc., 2012.

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15

Capiński, Marek. Measure, integral, and probability. London: Springer, 1999.

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16

1944-, Kopp P. E., ed. Measure, integral and probability. 2nd ed. London: Springer, 2004.

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17

C, Taylor J. An introduction to measure and probability. New York: Springer, 1997.

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18

Pandey, Rakesh Kumar. Encyclopaedia of Measure Theory. New Delhi, India: Anmol Publications Pvt. Ltd., 2009.

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19

Lukeš, Jaroslav. Measure and Integral. Prague, Czech Republic: Matfyzpress, 1995.

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20

Gentili, Stefano. Measure, Integration and a Primer on Probability Theory. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54940-4.

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21

Dubhashi, Devdatt. Concentration of measure for the analysis of randomized algorithms. Cambridge: Cambridge University Press, 2012.

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22

Edgar, Gerald A. Integral, Probability, and Fractal Measures. New York, NY: Springer New York, 1998.

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23

Number theoretic density and logical limit laws. Providence, RI: American Mathematical Society, 2001.

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24

Integral, probability, and fractal measures. New York: Springer, 1998.

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25

Donald C. Pierantozzi Sc D. Measure Theory And Lebesgue Integration. USA: Independently published, 2019.

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26

Charles University. Mathematics and Physics Faculty, ed. Measure and Integral: Third Edition. Prague, Czech Republic: Matfyzpress, 2013.

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27

Probability, random processes, and ergodic properties. New York: Springer-Verlag, 1988.

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28

Probability in Banach spaces--stable and infinitely divisible distributions. Chichester: Wiley, 1986.

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29

Concentration of measure for the analysis of randomized algorithms. Cambridge: Cambridge University Press, 2009.

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30

Mathai, A. M. An introduction to geometrical probability: Distributional aspects with applications. Amsterdam, USA: Gordon & Breach, 1999.

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31

M, Gray Robert. Probability, Random Processes, and Ergodic Properties. Boston, MA: Springer-Verlag US, 2009.

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32

Lectures on topics in probability inequalities. Amsterdam, Netherlands: Centrum voor Wiskunde en Informatica, 1987.

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33

service), SpringerLink (Online, ed. Measure-Valued Branching Markov Processes. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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34

Ma© und Wahrscheinlichkeit. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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35

Probability measures on metric spaces. Providence, R.I: AMS Chelsea Pub., 2005.

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36

Marc, Yor, ed. Exercises in probability: A guided tour from measure theory to random processes, via conditioning. Cambridge, U.K: Cambridge University Press, 2003.

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37

Chaumont, L. Exercises in probability: A guided tour from measure theory to random processes, via conditioning. 2nd ed. Cambridge: Cambridge University Press, 2012.

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38

Rosenthal, Jeffrey S. Gambling systems and multiplication-invariant measures. Toronto: University of Toronto, 1997.

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39

Gavriluţ, Alina. Atomicity Through Fractal Measure Theory: Mathematical and Physical Fundamentals with Applications. Cham, Switzerland: Springer Nature Switzerland AG 2019, 2019.

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40

Invariant measures on groups and their use in statistics. Hayward, Calif: Institute of Mathematical Statistics, 1990.

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41

Pawar, Akhilesh. Probability And Statistics. New Delhi, India: Campus Books International, 2011.

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42

service), SpringerLink (Online, ed. The Borel-Cantelli Lemma. India: Springer India, 2012.

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43

Bobkov, Serguei G. Some connections between isoperimetric and Sobolev-type inequalities. Providence, R.I: American Mathematical Society, 1997.

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44

Todorovic, P. Sets Measures Integrals. Bloomington, USA: Xlibris Corporation, 2012.

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45

Ambrosio, Luigi. Gradient flows: In metric spaces and in the space of probability measures. Basel: Birkhauser, 2004.

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46

Nicola, Gigli, and Savaré Giuseppe, eds. Gradient flows: In metric spaces and in the space of probability measures. Boston: Birkhäuser, 2005.

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47

Simonnet, Michel. Measures and probabilities. New York: Springer, 1996.

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48

André, Meyer Paul, and Meyer Paul André, eds. Probabilities and potential. Amsterdam: North-Holland Pub. Co., 1988.

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49

Liese, Friedrich. Convex statistical distances. Leipzig, Germany: Teubner, 1987.

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50

Roussas, George G. Introduction to Measure-Theoretic Probability. Elsevier Science & Technology Books, 2014.

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