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3. Newton’s Method and Scoring
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References
3.10
[1] Bernardo JM (1976) Algorithm AS 103: psi (digamma) function. Appl
Statist 25:315–317
[2] Bradley EL (1973) The equivalence of maximum likelihood and
weighted least squares estimates in the exponential family. J Amer
Stat Assoc 68: 199–200
[3] Charnes A, Frome EL, Yu PL (1976) The equivalence of generalized
least squares and maximum likelihood in the exponential family. J
Amer Stat Assoc 71:169–171
[4] Conn AR, Gould NIM, Toint PL (1991) Convergence of quasi-Newton
matrices generated by the symmetric rank one update. Math Prog
50:177–195
[5] Davidon WC (1959) Variable metric methods for minimization. AEC
Research and Development Report ANL–5990, Argonne National Lab-
oratory
[6] Edwards A, Hammond HA, Jin L, Caskey CT, Chakraborty R (1992)
Genetic variation at five trimeric and tetrameric tandem repeat loci
in four human population groups. Genomics 12:241–253

[7] Efron B, Hinkley DV (1978) Assessing the accuracy of the maximum
likelihood estimator: Observed versus expected Fisher information.
Biometrika 65:457–487

[8] Ferguson TS (1996) A Course in Large Sample Theory. Chapman &
Hall, London

[9] Hille E (1959) Analytic Function Theory Vol 1. Blaisdell Ginn, New
York

[10] Jennrich RI, Moore RH (1975) Maximum likelihood estimation by
means of nonlinear least squares. Proceedings of the Statistical Com-
puting Section: American Statistical Association 57–65

[11] Khalfan HF, Byrd RH, Schnabel RB (1993) A theoretical and experi-
mental study of the symmetric rank-one update. SIAM J Optimization
3:1–24
[12] Kingman JFC (1993) Poisson Processes. Oxford University Press, Ox-
ford

[13] Lange K (1995) Applications of the Dirichlet distribution to forensic
match probabilities. Genetica 96:107–117