Books on the topic 'Weibull distribution'

Dodson, Bryan. Weibull analysis. Milwaukee, Wis: ASQC Quality Press, 1994.

Dodson, Bryan. Weibull analysis. Milwaukee, Wis: ASQC Quality Press, 1994.

Murthy, D. N. P. Weibull models. Hoboken, N.J: J. Wiley, 2004.

The Weibull distribution: A handbook. Boca Raton, Fla: Chapman & Hall/CRC, 2008.

Abernethy, Robert B. The new Weibull handbook. 3rd ed. North Palm Beach, Fla: R.B. Abernethy, 1998.

Abernethy, Robert B. The new Weibull handbook. 2nd ed. North Palm Beach, Fla: R.B. Abernethy, 1996.

McCool, John. Using the Weibull distribution: Reliability, modeling, and inference. Hoboken, N.J: John Wiley & Sons, 2012.

Yuhai, Mao, and Institution of Electrical Engineers, eds. Weibull radar clutter. London, UK: P. Peregrinus Ltd. on behalf of the Institution of Electrical Engineers, 1990.

McCool, John. Using the Weibull distribution: Reliability, modeling, and inference. Hoboken, N.J: John Wiley & Sons, 2012.

Savage, M. Transmission overhaul estimates for partial and full replacement at repair. [Washington, DC]: National Aeronautics and Space Administration, 1991.

Zaretsky, Erwin V. Fatigue criterion to system design, life and reliability--a primer. [Washington, DC: National Aeronautics and Space Administration, 1992.

Rheinfurth, M. Weibull distribution based on maximum likelihood with interval inspection data. [Marshall Space Flight Center, Ala.]: National Aeronautics and Space Administration, George C. Marshall Space Flight Center, 1985.

Duffy, Stephen F. Reliability analysis of structural ceramic components using a three-parameter Weibull distribution. [Washington, DC]: National Aeronautics and Space Administration, 1992.

A, Johnson Richard. Some bivariate distributions for modeling the strength properties of lumber. Madison, WI (One Gifford Pinchot Dr., Madison 53705-2398): U.S. Dept. of Agriculture, Forest Service, Forest Products Laboratory, 1999.

The new Weibull handbook: Reliability & statistical analysis for predicting life, safety, risk, support costs, failures, and forecasting warranty claims, substantiation and accelerated testing, using Weibull, Log normal, crow-AMSAA, probit, and Kaplan-Meier models. 5th ed. North Palm Beach, Fla: R.B. Abernethy, 2006.

Gross, Bernard. Least squares best fit method for the three parameter Weibull distribution: Analysis of tensile and bend specimens with volume or surface flaw failure. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.

United States. National Aeronautics and Space Administration., ed. Lower bound on reliability for Weibull distribution when shape parameter is not estimated accurately. [Washington, DC: National Aeronautics and Space Administration, 1990.

Johnson, Richard Arnold. Some bivariate distributions for modeling the strength properties of lumber. Madison, WI: U.S. Dept. of Agriculture, Forest Service, Forest Products Laboratory, 1999.

Johnson, Richard Arnold. Some bivariate distributions for modeling the strength properties of lumber. Madison, WI (One Gifford Pinchot Dr., Madison 53705-2398): U.S. Dept. of Agriculture, Forest Service, Forest Products Laboratory, 1999.

Evans, James W. Censoring data for resistance factor calculations in load and resistance factor design: A preliminary study. Madison, WI: United States Dept. of Agriculture, Forest Service, Forest Products Laboratory, 2007.

Evans, James W. Censoring data for resistance factor calculations in load and resistance factor design: A preliminary study. Madison, WI: United States Dept. of Agriculture, Forest Service, Forest Products Laboratory, 2007.

Verrill, S. P. An evaluation of a proposed revision of the ASTM D 1990 grouping procedure. Madison, WI: United States Department of Agriculture, Forest Service, Forest Products Laboratory, 2013.

Johnson, Richard Arnold. Confidence intervals for predicting lumber strength properties based on ratios of percentiles from two Weibull populations. Madison, WI (One Gifford Pinchot Dr., Madison 53726-2398): U.S. Dept. of Agriculture, Forest Service, Forest Products Laboratory, 2003.

Johnson, Richard Arnold. Confidence intervals for predicting lumber strength properties based on ratios of percentiles from two Weibull populations. Madison, WI (One Gifford Pinchot Dr., Madison 53726-2398): U.S. Dept. of Agriculture, Forest Service, Forest Products Laboratory, 2003.

Johnson, Richard Arnold. Confidence intervals for predicting lumber strength properties based on ratios of percentiles from two Weibull populations. Madison, WI: U.S. Dept. of Agriculture, Forest Service, Forest Products Laboratory, 2003.

J, Hu, Hopkins D. A, and Lewis Research Center, eds. An overview of engineering concepts and current design algorithms for probabilistic structural analysis. Cleveland, Ohio: NASA Lewis Research Center, 1995.

Lai, Chin-Diew. Generalized Weibull Distributions. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-39106-4.

Güimil, Fernando. Comparing the Maximum Likelihood Method and a Modified Moment Method to fit a Weibull distribution to aircraft engine failure time data. Monterey, Calif: Naval Postgraduate School, 1997.

Lee, Hyeon-Soo. Approximate interval estimation methods for the reliability of systems using component data with exponential and Weibull distributions. Monterey, Calif: Naval Postgraduate School, 1989.

Rinne, Horst. Weibull Distribution. Taylor & Francis Group, 2008.

Rinne, Horst. Weibull Distribution. Taylor & Francis Group, 2020.

Rinne, Horst. The Weibull Distribution. Chapman and Hall/CRC, 2008. http://dx.doi.org/10.1201/9781420087444.

Rinne, Horst. Weibull Distribution: A Handbook. Taylor & Francis Group, 2008.

Rinne, Horst. Weibull Distribution: A Handbook. Taylor & Francis Group, 2008.

McCool, John I. Using the Weibull Distribution. Wiley & Sons, Incorporated, John, 2012.

Bhattacharya, Paritosh. Weibull Distribution for Estimating the Parameters. INTECH Open Access Publisher, 2011.

Dodson, Bryan. The Weibull Analysis Handbook. 2nd ed. ASQ Quality Press, 2006.

Abdelhafez, Mohamed Elwy Mahran. Bootstrap prediction and tolerance intervals for the Weibull regression model with censored data. 1989.

Generalized Weibull Distributions Springerbriefs in Statistics. Springer-Verlag Berlin and Heidelberg GmbH &, 2013.

Basu, P., and N. Balakrishnan. The Weibull Distribution: Theory, Methods and Applications. Gordon and Breach, 1997.

McCool, John I. Using the Weibull Distribution: Reliability, Modeling, and Inference. Wiley & Sons, Incorporated, John, 2012.

McCool, John I. Using the Weibull Distribution: Reliability, Modeling, and Inference. Wiley & Sons, Limited, John, 2012.

McCool, John I. Using the Weibull Distribution: Reliability, Modeling, and Inference. Wiley & Sons, Incorporated, John, 2012.

McCool, John I. Using the Weibull Distribution: Reliability, Modeling, and Inference. Wiley & Sons, Incorporated, John, 2012.

Weibull distribution based on maximum likelihood with interval inspection data. [Marshall Space Flight Center, Ala.]: National Aeronautics and Space Administration, George C. Marshall Space Flight Center, 1985.

Eng, Helge. Weibull diameter distribution models for managed stands of Douglas-fir in Washington and Oregon. 1985.

A comparison of Weibull and [beta]I đc analysis of transition range fracture toughness data. Washington, DC: Division of Engineering, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1992.

Least squares best fit method for the three parameter Weibull distribution: Analysis of tensile and bend specimens with volume or surface flaw failure. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1996.

Birke, Hanna. Model-Based Recursive Partitioning with Adjustment for Measurement Error: Applied to the Cox’s Proportional Hazards and Weibull Model. Springer Spektrum, 2015.

Birke, Hanna. Model-Based Recursive Partitioning with Adjustment for Measurement Error: Applied to the Cox's Proportional Hazards and Weibull Model. Springer Vieweg. in Springer Fachmedien Wiesbaden GmbH, 2015.