R3(References on References on References) on "What are the most important statistical ideas of the past 50 years? " Andrew Gelman, Aki Vehtari(44)
R3(0) on "What are the most important statistical ideas of the past 50 years? " Andrew Gelman, Aki Vehtari
https://qiita.com/kaizen_nagoya/items/a8eac9afbf16d2188901
What are the most important statistical ideas of the past 50 years?
Andrew Gelman, Aki Vehtari
https://arxiv.org/abs/2012.00174
References 44
Efron, B., and Tibshirani, R. J. (1993). An Introduction to the Bootstrap. London: Chapman and Hall.
REFERENCE ON 44
44.1
Abramovitch, L. and Singh, K. (1985) Edgeworth corrected pivotal statistics and the bootstrap. Ann. Statist. 13, 116-132.
REFERENCE ON 44.1
44.1.1
BABU, G. J. and SINGH, K. (1982). Edgeworth expansions for sampling without replacement from finite populations. J. Multivariate Anal., to appear.
44.1.2
BABU, G. J. AGE SINGH, K. (1983). Inference on means using the bootstrap. Ann. Statist. 11, 999-1003.
44.1.3
BHATTACHARYA, R. N. and GHOSH, J. K. (1978). On the validity of formal Edgeworth expansion. Arm. Statist. 6 434-451.
44.1.4
EFRON, B. (1979). Bootstrap methods: Another look at the jackknife. Arm. Statist. 71-26.
44.1.5
HALL, P. (1983). Inverting an Edgeworth expansion. Arm. Statist. 11 569-576.
44.1.6
JOHNSON, N. J. (1978). Modified t-tests and confidence intervals for asymmetrical population. J. Amer. Statist. Assoc. 73 536-544.
44.1.7
SINGH, K. (1981). On asymptotic accuracy of Efron's bootstrap. Arm. Statist. 9 1187-1195.
44.1.8
WITHERS, C. S. (1983). Expansion for the distribution and guantilea of a regular functional of the empirical distribution with applications to non-parametric confidence intervals. Arm. Statist. 11 577-587.
44.2
Akaike, H. (1973) Information theory and an extension of the maxi- mum likelihood principle. In Second International Symposium on In- formation Theory, (eds. B.N. Petrov and F. Czaki) Akademiai Kiad6, Budapest, 267-81.
44.3
Allen, D.M. (1974) The relationship between variable selection and data augmentation and a method of prediction. Technometrics 16, 125-7.
44.4
Anderson, T.W. (1958) An introduction to multivariate statistical analysis. Wiley, New York.
44.5
Bai, C., Bickel, P.J., and Olshen, R.A. (1990) Hyperaccuracy of boot-
strap based prediction. Probability in Banach Spaces VII Proceed- ings of the Seventh International Conference (edited by E. Eberlein, J. Kuelbs, and M.B. Marcus), Birkhauser Boston, Cambridge, Mas- sachusetts, 31-42.
44.6
Bai. C, and Olshen, R.A. (1988) Discussion of "Theoretical comparison of bootstrap confidence intervals" by P. Hall, Ann. Statist. 16, 953- 956.
44.7
Barnard, G.A. (1963) Contribution to discussion. J. Royal. Statist. Soc. B 25, 294.
44.8
Barndorff-Neilson, O.E. and Cox, D.R. (1989) Asymptotic techniques for use in statistics. Chapman and Hall, London, New York.
44.9
Becker, R., Chambers, J. and Wilks. A. (1988) The S language. Wadsworth, Belmont CA.
44.10
Behrens, B.-U. (1929) Ein Beitrag zur Fehlen-Berechnung bei wenigen Beobachtungen. Landwirtsch. Jb. 68, 807-837.
44.11
Beran, R. (1984) Bootstrap methods in statistics. Jber. d. Dt. Math. Verein. 86, 14-30.
44.12
Beran, R. (1987) Prepivoting to reduce level error of confidence sets. Biometrika 74, 457-468.
44.13
Beran, R. (1988) Prepivoting test statistics: a bootstrap view of asymp- totic refinements, J. Amer. Statist. Assoc. 83, 687-697.
44.14
Beran, R. and Ducharme, G. (1991) Asymptotic theory for bootstrap methods in statistics. Centre de Reserches Mathematiques, Univ. of Montreal.
44.15
Beran, R. and Millar, P.W. (1987) Stochastic estimation and testing.
Ann. Statist. 15, 1131-1154.
44.16
Beran, R. and Srivastava, M.S. (1985) Bootstrap tests and confidence
regions for functions of a covariance matrix. Ann. Statist. 13, 95-115.
44.17
Besag, J. and Clifford, P. (1989) Generalized Monte Carlo significance
tests. Biometrika 76, 633-642.
44.18
Bickel, P.J. and Freedman, D.A. (1981) Some asymptotic theory for the
bootstrap. Ann. Statist. 9, 1196-1217.
44.19
Bickel, P.J. and Freedman, D.A. (1983) Bootstrapping regression mod-
els with many parameters, A Festschrift for Erich L. Lehmann, P.J.
44.20
Bickel, K. Doksum and J.L. Hodges eds., Wadsworth, Belmont, CA.
44.21
Bickel, P.J. and Freedman, D.A. (1984) Asymptotic normality and the
bootstrap in stratified sampling, Ann. Statist. 12, 470-482.
44.22
Boos, D. and Monahan, J. (1986) Bootstrap methods using prior infor-
mation. Biometrika 73, 77-83
44.23
Box, G.E. and Jenkihs, G.M (1970) Times series analysis, forecasting,
and control. Holden-Day, San Francisco.
44.24
Breiman, L. (1992) The little bootstrap and other methods for dimen-
sionality selection in regression: X-fixed prediction error. J. Amer.
Statist. Assoc. 87, 738-754.
44.25
Breiman, L., Friedman, J., Olshen, R., and Stone, C. (1984) Classifi-
cation and Regression Trees. Wadsworth, Belmont, CA.
44.26
Breiman, L. and Spector, P. (1992) Submodel selection and evaluation
in Regression. The X-Random Case. Int. Stat. Rev. 60, 291-319.
44.27
Buckland, S.T. (1983) Monte Carlo methods for confidence interval es- timation using the bootstrap technique. Bull. Appl. Statist. 10, 194-212.
44.28
Buckland, S.T. (1984) Monte Carlo confidence intervals. Biometrics 40,811-817.
44.29
Buckland, S.T. (1985) Calculation of Monte Carlo confidence intervals.
Appl. Statist. 34, 296-301.
44.30
Carlstein, E. (1986) The use of subseries values for estimating the vari-
ance of a general statistic from a stationary sequence. Ann. Statist.
14, 1171-1179.
44.31
Chambers, J. and Hastie. T.J. (eds) (1991) Statistical models in S.
Wadsworth, Belmont, CA.
44.32
Chatfield, C. (1980) The analysis of time series: an introduction (second
edition). Chapman and Hall, London.
44.33
Cleveland, W.S. (1979) Robust locally-weighted regression and smooth-
ing scatterplots. J. Amer. Statist. Assoc. 74, 829-36.
44.34
Cox, D.R. and Hinkley, D.V. (1974) Theoretical Statistics. Chapman and Hall, London.
44.35
Cox, D.R. and Reid, N. (1987) Orthogonal parameters and approximate conditional inference (with discussion) J. Royal. Statist. Soc. B 49, 1-39.
44.36
Cox, D. R. and Snell. E.J. (1981) Applied statistics. Principles and ex- amples. Chapman and Hall, London.
44.37
Crawford, S. (1989) Extensions to the CART algorithm. Int. J. of Ma- chine Studies 31, 197-217.
44.38
Davison, A.C. (1988) Discussion of papers by D.V. Hinkley and by T.J. DiCiccio and J.P. Romano. J. Royal. Statist. Soc. B 50, 356-357.
44.39
Davison A.C. and Hinkley, D.V. (1988) Saddlepoint approximations in resampling methods. Biometrika 75, 417-431.
44.40
Davison A.C., Hinkley, D.V. and Schechtman, E. (1986) and Efficient
bootstrap simulations, Biometrika 73. 555-566.
44.41
Davison A.C., Hinkley, D.V. and Worton, B.J. (1992) Bootstrap likeli-
hoods, Biometrika 19, 113-130.
44.42
Devroye, L. (1986) Non-uniform random variate generation. Springer,
Berlin, New York.
44.43
Diaconis, P. and Efron, B. (1983) Computer-intensive methods in statis-
tics. Sci. Amer. 248, 116-130.
44.44
DiCiccio, T.J. Hall, P. and Romano, J.P. (1989b) Comparison of para-
metric and empirical likelihood functions. Biometrika 16, 465-476.
44.45
DiCiccio, T.J., Martin, M. and Young, A. (1992) Analytic approxima- tions to bootstrap distribution functions using saddlepoint methods. Tech. report, Stanford University.
44.46
DiCiccio, T .J. and Romano, J.P . (1988) A review of bootstrap confidence
intervals (with discussion). J. Royal. Statist. Soc. B 50, 338-370.
44.47
DiCiccio, T.J. and Romano, J.P. (1989) The automatic percentile method: Accurate confidence limits in parametric models, Can. J. Statist. 17, 155-169.
44.48
DiCiccio, T.J. and Romano, J.P. (1990) Nonparametric confidence limits
by resampling methods and least favorable families, Inter. Statist.
Review 58, 59-76.
44.49
DiCiccio, T.J. and Tibshirani, R. (1987) Bootstrap confidence intervals
and bootstrap approximations. J. Amer. Statist. Assoc. 82, 163-170.
44.50
Diggle, P. (1990) Time Series, a Biostatistical Introduction. Clarendon
Press, Oxford.
44.51
Do, K.A. and Hall, P. (1991) On importance resampling for the boot-
strap, Biometrika 78, 161-167.
44.52
Draper, N. and Smith, H. (1981) Applied regression analysis, (second
edition). Wiley, New York.
44.53
Ducharme, G.R., Jhun, M., Romano, J.P., and Truong, K.N. (1985)
Bootstrap confidence cones for directional data. Biometrika 72, 637-645.
44.54
Edgington, E.S. (1987) Randomization Tests, 2nd ed. Dekker, New York.
44.55
Efron, B. (1979a) Bootstrap methods: another look at the jackknife. Ann. Statist. 7, 1-26.
44.56
Efron, B. (1979b) Computers and the theory of statistics: thinking the unthinkable. SIAM Review 21, 46Q-480.
44.57
Efron, B. (1981a) Nonparametric standard errors and confidence inter- vals. (With discussion.) Can. J. Statist. 9, 139-172.
44.58
Efron, B. (1981b) Nonparametric estimates of standard error: the jack- knife, the bootstrap, and other methods. Biometrika 68, 589-599.
44.59
Efron, B. (1982) The jackknife, the bootstrap and other resampling
plans. Volume 38 of GEMS-NSF Regional Conference Series in Applied Mathematics. SIAM.
44.60
Efron, B. (1983) Estimating the error rate of a prediction rule: improve-
ments on cross-validation. J. Amer. Statist. Assoc. 78, 316-331.
44.61
Efron, B. (1985) Bootstrap confidence intervals for a class of parametric
problems. Biometrika 72, 45-58.
44.62
Efron, B. (1986) How biased is the apparent error rate of a prediction
rule? J. Amer. Statist. Assoc. 81, 461-70.
44.63
Efron, B. (1987) Better bootstrap confidence intervals. (with discussion.)
J. Amer. Statist. Assoc. 82, 171-200.
44.64
Efron, B. (1988) Bootstrap confidence intervals: good or bad? (With
discussion.) Psychol. Bull. 104, 293-296.
44.65
Efron, B. (1990) More efficient bootstrap computations. J. Amer.
Statist. Assoc. 85, 79-89.
44.66
Efron, B. (1991) Regression percentiles using asymmetric squared error
loss. Statistica Sinica 1, 93-125.
44.67
Efron, B. (1992a). Six questions raised by the bootstrap. Exploring the
Limits of Bootstrap (Eds. R. LePage and L. Billard), John Wiley and
Sons, 99-126, New York.
44.68
Efron, B. (1992b) Jacknife-after-bootstrap standard errors and influence
functions. J. Royal. Statist. Soc. B 54, 83-127.
44.69
Efron, B. (1992c) Bayes and likelihood calculations from confidence in-
tervals. Tech, rep., Dept. of Statistics, Stanford Univ.
44.70
Efron, B. and Feldman, D. (1991) Compliance as an explanatory variable
in clinical trials. J. Amer. Statist. Assoc. 86, 9-26.
44.71
Efron, B. and Gong, G. (1983) A leisurely look at the bootstrap, the
jackknife and cross-validation. Amer. Statistician 37, 36-48.
44.72
Efron, B. and Stein, C. (1981) The jackknife estimate of variance, Ann.
Statist. 9, 586-596.
44.73
Efron, B. and Tibshirani, R. (1985) The bootstrap method for assessing
statistical accuracy. Behaviormetrika 17, 1-35.
44.74
Efron, B. and Tibshirani, R. (1986) Bootstrap measures for standard
errors, confidence intervals, and other measures of statistical accuracy.
Statistical Science 1, 54-77.
44.75
Efron, B. and Tibshirani, R. (1991) Statistical data analysis in the
computer age. Science 253, 390-395.
44.76
Eubank, R.L. (1988) Smoothing Splines and Nonparametric Regression. Marcel Dekker, New York and Basel.
44.77
Faraway, J. and Jhun, M. (1990) Bootstrap choice of bandwidth for density estimation. J. Amer. Statist. Assoc. 85, 1119-1122.
44.78
Fernholz, L.T. (1983). Von Mises calculus for statistical functionals. Lec- ture Notes in Statistics, 19, Springer, New York.
44.79
Feuerverger, A. (1989) On the empirical saddlepoint approximation. Biometrika 76, 457-464.
44.80
Fisher, N.l. and Hall, P. (1989) Bootstrap confidence regions for direc- tional data. J. Amer. Statist. Assoc. 84, 996-1002.
Fisher, N.l. and Hall, P. (1990) On bootstrap hypothesis testing. Austral. J. Statist. 32, 177-190.
Freedman, D.A. (1981) Bootstrapping regression models. Ann. Statist. 9, 1218-1228.
Freedman, D.A. and Peters, S.C. (1984) Bootstrapping a regression equation: Some empirical results. J. Amer. Statist. Assoc. 79, 97- 106.
Giampaolo, C., Gray, A., Olshen, R. and Szabo, S. (1988) Predicting induced duodenal ulcer and adrenal necrosis with classification trees. Technical Report 125, Division of Biostatistics, Stanford University.
Gine, E. and Zinn, J. (1989) Necessary conditions for the bootstrap of the mean, Ann. Statist. 17, 684-691.
Gine, E. and Zinn, J. (1990) Bootstrap general empirical measures, Ann. Prob. 18, 851-869.
Gleason, J.R. (1988) Algorithms for balanced bootstrap simulations, Amer. Statist. 42, 263-266.
Godambe, V.P. (1960) An optimum property of regular maximum like- lihood estimation. Ann. Math. Statist. 31, 1208-1211.
Godambe, V.P. (ed.) (1991) Estimating functions. Clarendon Press, Ox- ford.
Godambe, V.P. and Thompson, M.W. (1984) Robust estimation through estimating equations. Biometrika 71, 115-125.
Golub, G., Heath, M., and Wahba, G. (1979) Generalized cross valida- tion as a method for choosing a good ridge parameter. Technometrics 21, 215-224.
Golub, G. and Van Loan, C. V. (1983) Matrix computations. Johns Hopkins University Press.
Graham, R.L., Hinkley, D.V., John, P.W.M. and Shi, S. (1990) Balanced design of bootstrap simulations. J. Royal. Statist. Soc. B 52, 185-202. Gray, H.L. and Schucany, W.R. (1972) The Generalized Jackknife Statis-
tics, Marcel Dekker, New York.
Gross, S. (1980) Median estimation in sample surveys. Proc. Sect. Survey
Res. Methods, Amer. Stat. Assoc., 181-184.
Hall, P. (1986a) On the bootstrap and confidence intervals. Ann. Statist.
14, 1431-1452.
Hall, P. (1986b) On the number of bootstrap simulations required to construct a confidence interval. Ann. Statist. 14, 1453-1462.
Hall, P. (1987) On the bootstrap and likelihood-based confidence inter- vals. Biometrika 74, 481-493.
Hall, P. (1988a) Theoretical comparison of bootstrap confidence inter- vals. (with discussion.) Ann. Statist. 16, 927-953.
Hall, P. (1988b) On symmetric bootstrap confidence intervals. J. Royal. Statist. Soc. B 50, 35-45.
Hall, P. (1989a) On efficient bootstrap simulation. Biometrika 76, 613- 617.
Hall, P. (1989b) Antithetic resampling for the bootstrap. Biometrika 76, 713-724.
Hall, P. (1990) Performance of bootstrap balanced resampling in dis- tribution function and quantile problems. Prob. Th. Rel. Fields 85, 239-267.
Hall, P. (1991) Bahadur representations for uniform resampling and importance resampling, with applications to asymptotic relative ef- ficiency. Ann. Statist. 19, 1062-1072.
Hall, P. (1992) The Bootstrap and Edgeworth Expansion. Springer- Verlag, New York, Berlin, Heidelberg, London, Paris, Toyko, Hong Kong, Barcelona, Budapest.
Hall, P., DiCiccio, T.J. and Romano, J.P. (1989) On smoothing and the bootstrap. Ann. Statist. 17, 692-704.
Hall, P. and La Scala, B. (1990) Methodology and algorithms of empir- ical likelihood. Internat. Statist. Rev. 58, 109-127.
Hall, P. and Martin, M.A. (1988) On bootstrap resampling and iteration. Biometrika 75, 661-671.
Hall, P. and Titterington, D. (1987) Common structure of techniques for choosing smoothing parameters in regression problems. J. Royal. Statist. Soc. B 49, 184-198.
Hall, P. and Titterington, M. (1988) On confidence bands in nonpara- metric density estimation and regression. J. Mult. Anal. 27, 228-254. Hall, P. and Titterington, M. (1989) The effect of simulation order on level accuracy and power of Monte Carlo tests. J. Royal. Statist. Soc.
B 51, 459-467.
Hall, P. and Wilson, S.R. (1991) Two guidelines for bootstrap hypothesis
testing. Biometrics 47, 757-762.
Hammersley, J.M. and Handscomb, D.C. (1964) Monte Carlo Methods.
Methuen, London.
Hampel, F.R. (1974) The influence curve and its role in robust estima-
tion. J. Amer. Statist. Assoc. 69, 383-393.
Hampel, F.R., Ronchetti, E. M., Rousseeuw, P.J. and Stahel, W. A.
(1986) Robust statistics: The approach based on influence functions. Wiley, New York.
Hardie, W. (1990) Applied Non-parametric Regression. Oxford Univer- sity Press.
Hardie, W. and Bowman, A. (1988) Bootstrapping in nonparametric regression: local adaptive smoothing and confidence bands. J. Amer. Statist. Assoc. 83, 102-110
Hardie, W., Hall, P., and Marron, S. (1988) How far are automatically chosen smoothing parameters from their optimum? J. Amer. Statist. Assoc. 83, 86-95, Rejoinder 100-101.
Hartigan, J.A. (1969) Using subsample values as typical values. J. Amer. Statist. Assoc. 64, 1303-1317.
Hartigan, J.A. (1971) Error analysis by replaced samples. J. Royal. Statist. Soc. B 33, 98-110.
Hartigan, J.A. (1975) Necessary and sufficient conditions for asymptotic joint normality of a statistic and its subsample values. Ann. Statist. 3, 573-580.
Hartigan, J .A. (1986) Discussion of Efron and Tibshirani (1986). Statis- tical Science 1, 75-77.
Hastie, T. and Tibshirani, R. (1990) Generalized additive models. Chap- man and Hall, London.
Hesterberg, T. (1988) Advances in importance sampling. Ph.D. disser- tation, Dept. of Statistics, Stanford University.
Hesterberg, T. (1992) Efficient bootstrap simulations 1: Importance sam- pling and control variates. Unpublished.
Hinkley, D.V. (1977) Jackknifing in unbalanced situations. Technometics 19, 285-292.
Hinkley, D.V. (1988) Bootstrap methods (with discussion). J. Royal. Statist. Soc. B 50, 321-337.
Hinkley, D.V. (1989) Bootstrap significance tests, Proceedings of the 47th session of International Statistical Institute. Paris, 65-74.
Hinkley, D.V. and Shi, S. (1989) Importance sampling and the nested bootstrap. Biometrika 76, 435-446.
Hinkley, D.V. and Wei, B.C. (1984) Improvement ofjackknife confidence limit methods. Biometrika 11, 331-339.
Huber, P. J. (1981) Robust Statistics. Wiley, New York.
Hope, A.C.A. (1968) A simple Monte Carlo test procedure. J. Royal.
Statist. Soc. B 30, 582-598.
lzenman, A.J. and Sommer, C.J. (1988) Philatelic mixtures and multi-
modal densities. J. Amer. Statist. Assoc. 83, 941-953.
Jaeckel, L. (1972) The infinitesimal jackknife. Memorandum, MM 72-
1215-11, Bell Lab. Murray Hill, N.J.
Jeffreys, H. (1961) Theory of probability, 3rd Edition. Oxford, Clarendon
Press.
Johns, M.V. Jr. (1988) Importance sampling for bootstrap. confidence
intervals. J. Amer. Statist. Assoc. 83, 709-714.
Kendall, M.G. and Stuart, A. (1977) The Advanced Theory of Statistics, 4th Edition. Griffin, London.
Kent, T. J. (1982) Robust Properties of Likelihood Ratio Tests.
Biometrika 69, 19~27.
Kiefer, J. and Wolfowitz, J. (1956) Consistency of the maximum likeli-
hood estimator in the presence of infinitely many incidental parame-
ters. Ann. Math. Statist. 27, 887-906,
Kish, L. and Frankel, M.R. (1974) Inference from complex samples (with
discussion). J. Royal. Statist. Soc. B 36, 1~37.
Knuth, D. (1969) The art of computer programming. Addison-Wesley,
Reading, Mass.
Knuth, D. (1986) The TF;X book. Addison-Wesley, Reading, Mass. Kolaczyk, E. (1993) Empirical likelihood for generalized linear models.
To appear, Statist. Sinica.
Konishi, S. (1991) Normalizing transformations and bootstrap confi-
dence intervals, Ann. Statist. 19, 2209~2225.
Krewski, D. and Rao, J.N.K. (1981) Inference from stratified samples:
properties of the linearization, jackknife and balanced repeated repli-
cation methods, Ann. Statist. 9, 1010~1019.
Kiinsch, H. (1989) The jackknife and the bootstrap for general stationary
observations. Ann. Statist. 17, 1217-1241.
Laird, N. and Louis, T.A. (1987) Empirical Bayesian confidence intervals
based on bootstrap sampling. J. Amer. Statist. Assoc. 82, 739~750. Lamport, L. (1986) 11\TEX: a document preparation system. Addison-
Wesley. Reading, Mass.
Leger, C., Politis, D. and Romano, J. (1992) Bootstrap technology and
applications. Technometrics 34, 378~398.
Lehmann, E.L. (1983) Theory of Point Estimation . Wiley, New York. Lele, S. (1991) Resampling using estimating equations. In Estimating
functions, 295~304. V. Godambe ed. Clarendon Press, Oxford.
Lin, D. Y. and Wei, L. J. (1989) Robust Inference for the Cox Propor-
tional Hazards Model. J. Amer. Statist. Ass. 84, 1074~8.
Lindley, D.V. (1958) Fiducial distributions and Bayes theorem. J. Royal.
Statist. Soc. B 20, 102~107.
Linhart, H. and Zucchini, W. (1986) Model selection. Wiley, New York. Liu, R. Y. and Singh, K. (1992) Moving blocks jackknife and bootstrap
capture weak dependence. In Exploring the limits of bootstrap, ed. by
LePage and Billard. John Wiley, New York.
Lob, W.-Y. (1987) Calibrating confidence coefficients. J. Amer. Statist.
Assoc. 82, 155~162.
Loh, W.-Y. (1991) Bootstrap calibration for confidence interval con-
struction and selection, Statist. Sinica 1, 479~495.
Lunneborg, C.E. (1985) Estimating the correlation coefficient: The boot-
strap approach. Psychol. Bull. 98, 209~215.
Mallows, C. (1973) Some comments on Cp. Technometrics 15, 661~675.
Mardia, K.V ., Kent, J.T . and Bibby, J.M. (1979) Multivariate Analysis. Academic Press.
Martin, M.A. (1990) On bootstrap iteration for converge correction in confidence intervals. J. Amer. Statist. Assoc. 85, 1105-1108.
Marriot, F.H.C. (1979) Barnard's Monte Carlo test: how many simula- tions? Appl. Statist. 28, 75-77.
McCarthy, P.J. (1969) Pseudo-replication: half samples. Rev. Internat. Statist. Inst. 37, 239-264.
McKay, M.D. Beckman, R.M. and Conover, W.J. (1979) A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 21, 239-245.
Miller, R.G. (1964) A trustworthy jackknife. Ann. Math. Statist. 39, 1594-1605.
Miller, R.G. (1974) The jackknife- a review. Biometrika 61, 1-17. Morrison, D.F. (1976) Multivariate statistical methods, 2nd Ed.
McGraw-Hill, New York.
Newton, M., and Raftery, A. (1993) Approximate Bayesian inference
via the weighted likelihood bootstrap (with discussion) To appear, J.
Royal. Statist. Soc. B.
Noreen, E.W. (1989) Computer Intensive Methods for Testing Hypothe-
ses: An Introduction. Wiley, New York.
Ogbonmwan, S.M. and Wynn, H.P. (1988) Resampling generated likeli-
hoods. Statistical Decision Theory and Related Topics IV. S.S. Gupta
and J.O. Berger, eds.), Springer-Verlag, New York, pp. 133-147. Oldford, R.W . (1985) Bootstrapping "\JY Monte Carlo versus approximat- ing the estimator and bootstrapping exactly: Cost and performance.
Comm. Statist. Ser. B 14, 395-242.
Owen, A.B. (1988) Empirical likelihood ratio confidence intervals for a
single functional. Biometrika 75, 237-249.
Owen, A.B. (1990) Empirical likelihood confidence regions. Ann. Statist.
18, 90-120.
Parr, W.C. (1983) A note on the jackknife, the bootstrap and delta
method estimators of bias and variance. Biometrika 70, 719-722. Parr, W.C. (1985) Jackknifing differentiable statistical functionals. J.
Royal. Statist. Soc. B 47, 56-66.
Peters, S.C. and Freedman, D.A. (1984a) Bootstrapping an econometric
model: Some empirical results. J. Bus. Econ. Studies 2, 150-158. Peters, S.C. and Freedman, D.A. (1984b) Some notes on the bootstrap
in regression problems. J. Bus. Econ. Studies 2, 406-409.
Peters, S.C. and Freedman, D.A. (1987) Balm for bootstrap confidence
intervals. J. Amer. Statist. Assoc. 82, 186-187.
Politis, D. and Romano, J. (1992) The stationary bootstrap. Unpub-
lished.
Qin, J. and Lawless, J. (1993) Empirical likelihood and general estimat-
ing equations. To appear, Ann. Statist.
Quenouille, M. (1949) Approximate tests of correlation in time series. J. Royal. Statist. Soc. B 11, 18-44.
Rao, J.N.K. and Wu, C.F.J. (1985) Inference from stratified samples: second-order analysis of three methods for nonlinear statistics. J. Amer. Statist. Assoc. 80, 62Q--630.
Rao, J.N.K. and Wu, C.F.J. (1988) Resampling inference with complex survey data. J. Amer. Statist. Assoc. 83, 231-241.
Rasmussen, J. (1987) Estimating correlation coefficients: bootstrap and parametric approaches. Psych. Bull. 101, 136-139.
Reeds, J.A. (1978) Jackknifing maximum likelihood estimates. Ann. Statist. 6, 727-739.
Reid, N. (1988) Saddlepoint methods and statistical inference (with dis- cussion). Statistical Science 3, 213-238.
Rice, J. (1984) Bandwidth choice for nonparametric regression. Ann. Statist. 12, 1215-1230.
Robinson, G.K. (1982) Behrens-Fisher Problem. In Encyclopedia of Sta- tistical Science, Vol. 1. Ed. S. Kotz and N.L. Johnson. Wiley, New York. pp. 205-209.
Robinson, J.A. (1986) Bootstrap and randomization confidence inter- vals. Proceedings of the Pacific Statistical Congress, 20-24 May 1985, Auckland (I.S. Francis, B.F.J. Manly, and F.C. Lam, eds.), North- Holland, Groningen, pages 49-50.
Robinson, J.A. (1987) Nonparametric confidence intervals in regression: The bootstrap and randomization methods. New Perspectives in The- oretical and Applied Statistics (M.L. Puri, J.P. Vilaplana, and W. Wertz, eds.), Wiley, New York, pages 243-256.
Romano, J.P . (1988) A bootstrap revival of some nonparametric distance tests. J. Amer. Statist. Assoc. 83, 698-708.
Romano, J.P. (1989) Bootstrap and randomization tests of some non- parametric hypotheses. Ann. Statist. 17, 141-159.
Rousseeuw, P. (1984) Least median of squares regression. J. Amer. Statist. Assoc. 79, 871-80.
Royall, R. M. (1986) Model robust confidence intervals using maximum likelihood estimators. Int. Statist. Rev. 54, 221-6.
Rubin, D.B. (1981) The Bayesian bootstrap. Ann. Statist. 9, 130-134. Schenker, N. (1985) Qualms about bootstrap confidence intervals. J.
Amer. Statist. Assoc. 80, 360-361.
Scholz, F.W. (1980) Towards a unified definition of maximum likelihood.
Can. J. Statist. 8, 193- 203.
Schwarz, G. (1978) Estimating the dimension of a model. Ann. Statist.
6, 461-464.
Scott. D. (1992) Multivariate density estimation: theory, practice and
visualization. Wiley, New York.
Sen, P.K. (1988) Functional jackknifing: rationality and general asymp-
totics. Ann. Statist. 16, 450-469.
Shao, J. (1988) On resampling methods for bias and variance in linear models. Ann. Statist. 16, 986-988.
Shao, J. (1991) Consistency of jackknife variance estimators. Statistics 22, 49-57.
Shao, J. (1993) Linear model selection via cross-validation. To appear
J. Amer. Statist. Assoc..
Shao, J. and Wu, C.F.J. (1989) A general theory for jackknife variance
estimation. Ann. Statist. 17, 1176-1197.
Sheather, S.J. (1987) Assessing the accuracy of the sample median: es-
timated standard errors versus interpolated confidence intervals. In Statistical Data Analysis Based on the L1-Norm. Ed. Y. Dodge, pages 203-215. North Holland, Amsterdam.
Shorack, G.P. (1982) Bootstrapping robust regression. Comm. Statist. A. 11, 961-972.
Silverman, B.W. (1981) Using kernel density estimates to investigate multimodality. J. Royal. Statist. Soc. B 43, 97-99.
Silverman, B.W. (1983) Some properties of a test for multimodality based on kernel density estimates. In Probability, Statistics, and Anal- ysis Eds. J.F.C. Kingman, and G.E.H. Reuter, 248-260. Cambridge Univ. Press, Cambridge, U.K.
Silverman, B.W. (1985) Some aspects of the spline smoothing approach to non-parametric regression curve fitting. J. Royal. Statist. Soc. B 36, 1-52.
Silverman, B.W. (1986) Density Estimation for Statistics and Data Analysis. Chapman and Hall, London.
Silverman, B.W. and Young, G.A. (1987) The bootstrap: to smooth or not to smooth? Biometrika 74, 469-479.
Silvey, S.D. (1975) Statistical inference. Chapman and Hall, London. Simon, J.L. and Bruce, P (1991) Resampling: a tool for everyday statis-
tical work. Chance 4, 22-32.
Singh, K. (1981) On the asymptotic accuracy of Efron's bootstrap. Ann.
Statist. 9, 1187-1195.
Sitter R. V. (1992) Bootstrap methods for survey data. Can. J. Statist.,
20, 135-154.
Sitter, R. V. (1993) Balanced repeated replications based on orthogonal
multi-arrays. To appear, Biometrika, 80
Snedecor, G.W. and Cochran, W.G. (1980) Statistical methods. Seventh
edition. Iowa State University.
Stein, C. (1956) Efficient nonparametric testing and estimation, Pro-
ceedings of the Third Berkeley Symposium, University of California
Press, 187-196, Berkeley.
Stein, M. (1987) Large sample properties of simulations using Latin
hypercube sampling. Technometrics 29, 143-151.
Stine, R.A. (1985) Bootstrap prediction intervals for regression. J. Amer.
Statist. Assoc. 80, 1026-1031.
Stone, M. (1974) Cross-validation choice and assessment of statistical predictions. J. Royal. Statist. Soc. B 36, 111-147.
Stone, M. (1977) An asymptotic equivalence of choice of model by cross- validation and Akaike's criterion. J. Royal. Statist. Soc. B 39, 44-7.
Swanepoel, J.W.H., Van Wyk, J.W.J., and Venter, J.H. (1983) Fixed width confidence intervals based on bootstrap procedures. Sequential Anal. 2, 289-310.
Taylor, C.C. (1989) Bootstrap choice of the smoothing parameter in kernel density estimation. Biometrika 76, 705-712.
Therneau, T. M. (1983) Variance reduction techniques for the bootstrap. Ph.D. thesis, Department of Statistics, Stanford University.
Thisted, R.A. (1986) Elements of statistical computing. Chapman and Hall, London.
Tibshirani, R. (1985) Bootstrapping computations. Proc. of the SAS Users group conference, Reno, Nevada.
Tibshirani, R. (1986) Bootstrap confidence intervals. Computer Science and Statistics: Proceedings of the 18th Symposium on the Interface (J.T. Boardman, ed.), Amer. Stat. Assoc. Washington, DC, pages 267-273.
Tibshirani, R. (1988) Variance stabilization and the bootstrap. Biometrika 75, 433-444.
Tibshirani, R. (1992) Comment on "Two guidelines for bootstrap hy- pothesis testing", by Hall, P. and Wilson, S.R. Biometrics 48, 969- 970.
Tukey, J.W. (1958) Bias and confidence in not quite large samples. (Ab- stract.) Ann. Math. Statist. 29, 614.
Wahba, G. (1980) Spline bases, regularization, and generalized cross validation for solving approximation problems with large quantities of noisy data. In Cheney, W ., editor, Approximation Theory III, pages 905-912. Academic Press.
Wahba, G. (1990) Spline Functions for Observational Data. CBMS-NSF Regional Conference series, SIAM. Philadelphia.
Wasserman, L. (1990) Belief functions and statistical inference. Can. J. Statist. 18, 193-196.
Wang, S.J. (1992) General saddlepoint approximations in the bootstrap. Statist. Prob. Letters 13, 61-66.
Weber, N.C. (1984) On resampling techniques for regression models.
Proceedings of the Pacific Statistical Congress, 20-24 May 1985, Auck- land (I.S. Francis, B.F.J. Manly, and F.c. Lam, eds.), North-Holland, Groningen, pp. 51-55.
Weisberg, S. (1980) Applied linear regression. Wiley, New York.
Welch, B.L. (1947) The generalization of "Student's" problem when sev- eral different population variances are involved. Biometrika 34, 28-35. White, H. (1981) Consequences and detection of misspecified nonlinear
regression Models. J. Amer. Statist. Assoc. 76, 419-33.
参考資料(References)
Data Scientist の基礎(2)
https://qiita.com/kaizen_nagoya/items/8b2f27353a9980bf445c
岩波数学辞典 二つの版がCDに入ってお得
https://qiita.com/kaizen_nagoya/items/1210940fe2121423d777
岩波数学辞典
https://qiita.com/kaizen_nagoya/items/b37bfd303658cb5ee11e
アンの部屋（人名から学ぶ数学：岩波数学辞典）英語(24)
https://qiita.com/kaizen_nagoya/items/e02cbe23b96d5fb96aa1
＜この記事は個人の過去の経験に基づく個人の感想です。現在所属する組織、業務とは関係がありません。＞
最後までおよみいただきありがとうございました。
いいね 💚、フォローをお願いします。
Thank you very much for reading to the last sentence.
Please press the like icon 💚 and follow me for your happy life.