ÁÖ | ³¯Â¥ | °ÀÇ ³»¿ë | Çٽɾî/ºñ°í |
1 |
| °ú¸ñ¼Ò°³. Á¦1Àå ³»¿ë (1.1, 1.2) | Kolmogorov axioms of probability, counting |
2 |
| Á¦1Àå ³»¿ë (1.3, 1.4, 1.5, 1.6) | conditional probability, random variables, distribution function |
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| Á¦1Àå ¿¬½À¹®Á¦ |
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3 |
| Á¦2Àå ³»¿ë (2.1, 2.2) | transformation, expected value |
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| Á¦2Àå ³»¿ë (2.3, 2.4, Miscellanea) | mgf, Lebesgue's convergence theorem |
4 |
| Á¦2Àå ¿¬½À¹®Á¦ |
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| Á¦3Àå ³»¿ë (3.2, 3.3) | binomial/normal/gamma distribution |
5 |
| Á¦3Àå ³»¿ë (3.4, 3.5, Miscellanea) | exponential family, Poisson postulate |
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| Á¦3Àå ¿¬½À¹®Á¦ |
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6 |
| Á¦4Àå ³»¿ë (4.1, 4.2) | joint/marginal/conditional distribution |
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| Á¦4Àå ³»¿ë (4.3, 4.4, 4.5) | Jacobian, mixture distribution |
7 |
| Á¦4Àå ³»¿ë (4.6, 4.7, 3.6, Miscellanea) | multinomial dist. Hölder's inequality |
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| Á¦4Àå ¿¬½À¹®Á¦ (1¹ø-30¹ø) |
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8 |
| Á¦4Àå ¿¬½À¹®Á¦ (31¹ø-65¹ø) |
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| Áß°£°í»ç |
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9 |
| Á¦5Àå ³»¿ë (5.1, 5.2, 5.3, 5.4) | t and F distribution, order statistics |
10 |
| Á¦5Àå ³»¿ë (5.5, 5.6, Miscellanea) | convergence in distribution, delta method |
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| Á¦5Àå ¿¬½À¹®Á¦ (1¹ø-30¹ø) |
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11 |
| Á¦5Àå ¿¬½À¹®Á¦ (31¹ø-) |
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| Á¦6Àå ³»¿ë (6.2) | sufficient/ancillary/complete statistics |
12 |
| Á¦6Àå ³»¿ë (6.3, 6.4): »ý·« °¡´É | likelihood principle, equivariance principle |
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| Á¦6Àå ¿¬½À¹®Á¦ |
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13 |
| Á¦7Àå ³»¿ë (7.2) (7.2.4´Â »ý·« °¡´É) | MME, MLE, Bayes estimators, EM algorithm |
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| Á¦7Àå ³»¿ë (7.3) | UMVUE |
14 |
| Á¦10Àå ³»¿ë (10.1) | asymptotic optimality of MLE |
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| Á¦7Àå ¿¬½À¹®Á¦ (1¹ø-30¹ø) |
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15 |
| Á¦7Àå ¿¬½À¹®Á¦ (31¹ø-66¹ø) |
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16 |
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Casella, G., and Berger, R. L. (2002). Statistical Inference, 2nd edition, Duxbury Press.
Âü°í¼Àû
Bickel, P. J., and Doksum, K. A. (1977). Mathematical Statistics: Basic Ideas and Selected Topics. Holden-Day.
Lehmann, E. L. (1983). Theory of Point Estimation. John Wiley & Sons.
Chung, K. L. (1974). A Course in Probability Theory, 2nd Edition. Academic Press.
Apostol, T. M. (1977). Mathematical Analysis, 2nd Edition. Addison-Wesley.
Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.