Statistical Science

A Conversation with David Findley

Tucker S. McElroy and Scott H. Holan

Full-text: Open access

Abstract

David Findley was born in Washington, DC on December 27, 1940. After attending high school in Lyndon, Kentucky, he earned a B.S. (1962) and M.A. (1963) in mathematics from the University of Cincinnati. He then lived in Germany, studying functional analysis under Gottfried Köthe, obtaining a Ph.D. from the University of Frankfurt in 1967. Returning to the United States, he served as a mathematics professor at the University of Cincinnati until 1975. Having transitioned from pure mathematics to statistical time series analysis, Findley took a new academic position at the University of Tulsa, during which time he interacted frequently with the nearby research laboratories of major oil companies and consulted regularly for Cities Service Oil Company (now Citgo). In 1980 he was invited to lead the seasonal adjustment research effort at the U.S. Census Bureau, and eventually rose to be a Senior Mathematical Statistician before his retirement in 2009. In 1966 he married Mary Virginia Baker, and they currently live in Washington, DC.

David Findley has published more than 40 journal articles and book chapters, as well as dozens of technical reports and conference proceedings, many of which are heavily cited and influential. He has also published two edited volumes (1978 and 1981) that have had a substantial impact on the field of time series analysis. Numerous honors and awards have accrued to him, including ASA Fellow (1987), the Julius Shiskin award (1996) and the U.S. Department of Commerce Gold Medal (1997).

Article information

Source
Statist. Sci. Volume 27, Number 4 (2012), 594-606.

Dates
First available in Project Euclid: 21 December 2012

Permanent link to this document
https://projecteuclid.org/euclid.ss/1356098558

Digital Object Identifier
doi:10.1214/12-STS388

Mathematical Reviews number (MathSciNet)
MR3025136

Zentralblatt MATH identifier
1331.62023

Keywords
Census Bureau diagnostics model selection seasonal adjustment signal extraction time series

Citation

McElroy, Tucker S.; Holan, Scott H. A Conversation with David Findley. Statist. Sci. 27 (2012), no. 4, 594--606. doi:10.1214/12-STS388. https://projecteuclid.org/euclid.ss/1356098558.


Export citation

References

  • [1] Akaike, H. (1980). Seasonal adjustment by a Bayesian modeling. J. Time Ser. Anal. 1 1–13.
  • [2] Anderson, T. W. (1971). The Statistical Analysis of Time Series. Wiley, New York.
  • [3] Bell, W. and Hillmer, S. (1984). Issues involved with the seasonal adjustment of economic time series. J. Bus. Econom. Statist. 2 291–320.
  • [4] Box, G. and Jenkins, G. (1976). Time Series Analysis. Holden-Day, San Francisco.
  • [5] Brillinger, D. R. (1975). Time Series: Data Analysis and Theory. SIAM, Philadelphia, PA.
  • [6] Cantor, J. L. and Findley, D. F. (2006). Recursive estimation of possibly misspecified MA(1) models: Convergence of a general algorithm. In Time Series and Related Topics, (H. C. Ho, C. K. Ing and T. L. Lai, eds.). Institute of Mathematical Statistics Lecture Notes—Monograph Series 52 20–47. IMS, Beachwood, OH.
  • [7] Durbin, J. (1960). The fitting of time-series models. Revue, Institut International de Statistique 28 233–243.
  • [8] Findley, D., ed. (1978). Applied Time Series Analysis. Academic Press, New York.
  • [9] Findley, D. (1981). Geometrical and lattice versions of Levinson’s general algorithm. In Applied Time Series Analysis, II (Tulsa, Okla., 1980) 327–354. Academic Press, New York.
  • [10] Findley, D., ed. (1981). Applied Time Series Analysis. II. Academic Press, New York.
  • [11] Findley, D. (1988). An analysis of AIC for linear stochastic regression and control. In Proceedings of the 1988 American Control Conference 1281–1288.
  • [12] Findley, D. (1991). Counterexamples to parsimony and BIC. Ann. Inst. Statist. Math. 43 505–514.
  • [13] Findley, D. (1991). Convergence of finite multistep predictors from incorrect models and its role in model selection. Note Mat. 11 145–155.
  • [14] Findley, D. and HOOD, C. (2000). X-12-ARIMA and its application to some Italian indicator series. In “Seasonal Adjustment Procedures – Experiences and Perspectives.”. Annali di Statistica Anno 129 Serie X 20 249–269.
  • [15] Findley, D. and Martin, D. (2006). Frequency domain analyses of SEATS and X-11/12-ARIMA seasonal adjustment filters for short and moderate-length time series. Journal of Official Statistics 22 1–34.
  • [16] Findley, D. and Monsell, B. (2009). Modeling stock trading day effects under flow day-of-week constraints. Journal of Official Statistics 25 415–430.
  • [17] Findley, D., Monsell, B., Bell, W., Otto, M. and Chen, B. (1998). New capabilities and methods of the X-12-ARIMA seasonal adjustment program. J. Bus. Econom. Statist. 16 127–177.
  • [18] Findley, D. and Parzen, E. (1995). A conversation with Hirotugu Akaike. Statist. Sci. 10 104–117.
  • [19] Findley, D., Pötscher, B. M. and Wei, C.-Z. (2001). Uniform convergence of sample second moments of families of time series arrays. Ann. Statist. 29 815–838.
  • [20] Findley, D., Pötscher, B. M. and Wei, C.-Z. (2004). Modeling of time series arrays by multistep prediction or likelihood methods. J. Econometrics 118 151–187.
  • [21] Findley, D. and Wei, C.-Z. (2002). AIC, overfitting principles, and the boundedness of moments of inverse matrices for vector autoregressions and related models. J. Multivariate Anal. 83 415–450.
  • [22] Hillmer, C. and Tiao, G. C. (1982). An ARIMA-model-based approach to seasonal adjustment. J. Amer. Statist. Assoc. 77 63–70.
  • [23] Levinson, N. (1947). The Wiener RMS (root mean square) error criterion in filter design and prediction. J. Math. Phys. 25 261–278.
  • [24] McElroy, T. S. and Findley, D. F. (2010). Selection between models through multi-step-ahead forecasting. J. Statist. Plann. Inference 140 3655–3675.
  • [25] Riesz, F. and Sz.-Nagy, B. (1955). Functional Analysis. Unger, New York.
  • [26] Robinson, E. A. (1980). Physical Applications of Stationary Time-Series. Macmillan Inc., New York.