Skip to main content
SpringerLink
Log in

Observed Data Techniques-Normal Approximation

  • Chapter
Tools for Statistical Inference

Part of the book series: Lecture Notes in Statistics ((LNS,volume 67))

  • 409 Accesses

Abstract

Let Y denote the data which can be scalar, vector valued or matrix valued and suppose that

$$Y\sim f(Y|\theta )$$

, where f(•\•) is a density function indexed by a parameter θ (scalar or vector).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 74.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Bishop, Y.M.M., Fienberg, S. and Holland, P. (1975). Discrete Multivariate Analysis, Cambridge: MIT Press.

    MATH  Google Scholar 

  • Box, G.E.P. and Tiao, G. (1973). Bayesian Inference in Statistical Analysis, Reading: Addison-Wesley.

    MATH  Google Scholar 

  • Cox, D.R. and Hinkley, D.V. (1974). Theoretical Statistics. London: Chapman and Hall.

    MATH  Google Scholar 

  • Efron, B. and Hinkley, D.V. (1978). “Assessing the Accuracy of the Maximum Likelihood Estimator: Observed Versus Expected Fisher Information”, Biometrika, 65, 457–482.

    Article  MathSciNet  MATH  Google Scholar 

  • Jeffreys, H. (1967). Theory of Probability, Oxford.

    Google Scholar 

  • Little, R.J.A. and Rubin, D.B. (1987). Statistical Analysis With Missing Data, New York: Wiley.

    MATH  Google Scholar 

  • McCullagh, R and Nelder, J.A. (1983). Generalized Linear Models, London; Chapman and Hall.

    MATH  Google Scholar 

  • Mendenhall, W.M., Parsons, J.T., Stringer, S.P., Cassissi, N.J. and Million, R.R. (1989). “T2 Oral Tongue Carcinoma Treated With Radiotherapy: Analysis of Local Control and Complications”, Radiotherapy and Oncology, 16, 275–282.

    Google Scholar 

  • Miller, R. (1980). Survival Analysis. New York: Wiley.

    Google Scholar 

  • Rao, C.R. (1973). Linear Statistical Inference and its Applications, New York: Wiley.

    Book  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Biostatistics, University of Rochester Medical Center, 14642, Rochester, NY, USA

    Martin A. Tanner

Authors
  1. Martin A. Tanner
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 1991 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Tanner, M.A. (1991). Observed Data Techniques-Normal Approximation. In: Tools for Statistical Inference. Lecture Notes in Statistics, vol 67. Springer, New York, NY. https://doi.org/10.1007/978-1-4684-0510-1_2

Download citation

  • DOI: https://doi.org/10.1007/978-1-4684-0510-1_2

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-97525-2

  • Online ISBN: 978-1-4684-0510-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation