Template:Lognormal distribution maximum likelihood estimation - Revision history

Lisa Hacker: Redirected page to The Lognormal Distribution

2012-08-03T09:01:30Z

Redirected page to The Lognormal Distribution

← Older revision		Revision as of 09:01, 3 August 2012
Line 1:		Line 1:
	~~===Maximum Likelihood Estimation===~~		#REDIRECT [[The_Lognormal_Distribution]]
	~~As it was outlined in Chapter~~ [[~~Parameter Estimation~~]], maximum likelihood estimation works by developing a likelihood function based on the available data and finding the values of the parameter estimates that maximize the likelihood function. This can be achieved by using iterative methods to determine the parameter estimate values that maximize the likelihood function. However, this can be rather difficult and time-consuming, particularly when dealing with the three-parameter distribution. Another method of finding the parameter estimates involves taking the partial derivatives of the likelihood equation with respect to the parameters, setting the resulting equations equal to zero, and solving simultaneously to determine the values of the parameter estimates. The log-likelihood functions and associated partial derivatives used to determine maximum likelihood estimates for the lognormal distribution are covered in [[Appendix: Distribution Log-Likelihood Equations]]
	.

	~~'''Note About Bias'''~~

	~~See the discussion regarding bias with the [[The Normal Distribution\|normal distribution]] for information regarding parameter bias in the lognormal distribution.~~

Harry Guo: /* Maximum Likelihood Estimation */

2012-02-13T22:01:46Z

Maximum Likelihood Estimation

← Older revision		Revision as of 22:01, 13 February 2012
Line 5:		Line 5:
	'''Note About Bias'''		'''Note About Bias'''

	See the discussion regarding bias with the [[The Normal ~~Distribuiton~~\|normal distribution]] for information regarding parameter bias in the lognormal distribution.		See the discussion regarding bias with the [[The Normal Distribution\|normal distribution]] for information regarding parameter bias in the lognormal distribution.

Harry Guo: /* Maximum Likelihood Estimation */

2012-02-13T22:01:25Z

Maximum Likelihood Estimation

← Older revision		Revision as of 22:01, 13 February 2012
Line 5:		Line 5:
	'''Note About Bias'''		'''Note About Bias'''

	See the discussion regarding bias with the normal distribution ~~in Chapter 8~~ for information regarding parameter bias in the lognormal distribution.		See the discussion regarding bias with the [[The Normal Distribuiton\|normal distribution]] for information regarding parameter bias in the lognormal distribution.

Harry Guo: /* Maximum Likelihood Estimation */

2012-02-13T22:00:21Z

Maximum Likelihood Estimation

← Older revision		Revision as of 22:00, 13 February 2012
Line 1:		Line 1:
	===Maximum Likelihood Estimation===		===Maximum Likelihood Estimation===
	As it was outlined in Chapter 3, maximum likelihood estimation works by developing a likelihood function based on the available data and finding the values of the parameter estimates that maximize the likelihood function. This can be achieved by using iterative methods to determine the parameter estimate values that maximize the likelihood function. However, this can be rather difficult and time-consuming, particularly when dealing with the three-parameter distribution. Another method of finding the parameter estimates involves taking the partial derivatives of the likelihood equation with respect to the parameters, setting the resulting equations equal to zero, and solving simultaneously to determine the values of the parameter estimates. The log-likelihood functions and associated partial derivatives used to determine maximum likelihood estimates for the lognormal distribution are covered in Appendix C.		As it was outlined in Chapter [[Parameter Estimation]], maximum likelihood estimation works by developing a likelihood function based on the available data and finding the values of the parameter estimates that maximize the likelihood function. This can be achieved by using iterative methods to determine the parameter estimate values that maximize the likelihood function. However, this can be rather difficult and time-consuming, particularly when dealing with the three-parameter distribution. Another method of finding the parameter estimates involves taking the partial derivatives of the likelihood equation with respect to the parameters, setting the resulting equations equal to zero, and solving simultaneously to determine the values of the parameter estimates. The log-likelihood functions and associated partial derivatives used to determine maximum likelihood estimates for the lognormal distribution are covered in [[Appendix: Distribution Log-Likelihood Equations]]
			.

	'''Note About Bias'''		'''Note About Bias'''

	See the discussion regarding bias with the normal distribution in Chapter 8 for information regarding parameter bias in the lognormal distribution.		See the discussion regarding bias with the normal distribution in Chapter 8 for information regarding parameter bias in the lognormal distribution.

Harry Guo at 18:29, 13 February 2012

2012-02-13T18:29:13Z

← Older revision		Revision as of 18:29, 13 February 2012
Line 3:		Line 3:

	'''Note About Bias'''		'''Note About Bias'''

	See the discussion regarding bias with the normal distribution in Chapter 8 for information regarding parameter bias in the lognormal distribution.		See the discussion regarding bias with the normal distribution in Chapter 8 for information regarding parameter bias in the lognormal distribution.

Harry Guo at 18:29, 13 February 2012

2012-02-13T18:29:05Z

← Older revision		Revision as of 18:29, 13 February 2012
Line 1:		Line 1:
	===Maximum Likelihood Estimation===		===Maximum Likelihood Estimation===
	As it was outlined in Chapter 3, maximum likelihood estimation works by developing a likelihood function based on the available data and finding the values of the parameter estimates that maximize the likelihood function. This can be achieved by using iterative methods to determine the parameter estimate values that maximize the likelihood function. However, this can be rather difficult and time-consuming, particularly when dealing with the three-parameter distribution. Another method of finding the parameter estimates involves taking the partial derivatives of the likelihood equation with respect to the parameters, setting the resulting equations equal to zero, and solving simultaneously to determine the values of the parameter estimates. The log-likelihood functions and associated partial derivatives used to determine maximum likelihood estimates for the lognormal distribution are covered in Appendix C.		As it was outlined in Chapter 3, maximum likelihood estimation works by developing a likelihood function based on the available data and finding the values of the parameter estimates that maximize the likelihood function. This can be achieved by using iterative methods to determine the parameter estimate values that maximize the likelihood function. However, this can be rather difficult and time-consuming, particularly when dealing with the three-parameter distribution. Another method of finding the parameter estimates involves taking the partial derivatives of the likelihood equation with respect to the parameters, setting the resulting equations equal to zero, and solving simultaneously to determine the values of the parameter estimates. The log-likelihood functions and associated partial derivatives used to determine maximum likelihood estimates for the lognormal distribution are covered in Appendix C.

			'''Note About Bias'''
			See the discussion regarding bias with the normal distribution in Chapter 8 for information regarding parameter bias in the lognormal distribution.

Harry Guo: moved Template:Ld maximum likelihood estimation to Template:Lognormal distribution maximum likelihood estimation

2012-02-10T23:19:19Z

moved Template:Ld maximum likelihood estimation to Template:Lognormal distribution maximum likelihood estimation

← Older revision	Revision as of 23:19, 10 February 2012
(No difference)

Nicolette Young: Created page with '===Maximum Likelihood Estimation=== As it was outlined in Chapter 3, maximum likelihood estimation works by developing a likelihood function based on the available data and findi…'

2012-01-04T18:34:15Z

Created page with '===Maximum Likelihood Estimation=== As it was outlined in Chapter 3, maximum likelihood estimation works by developing a likelihood function based on the available data and findi…'

New page

===Maximum Likelihood Estimation===
As it was outlined in Chapter 3, maximum likelihood estimation works by developing a likelihood function based on the available data and finding the values of the parameter estimates that maximize the likelihood function. This can be achieved by using iterative methods to determine the parameter estimate values that maximize the likelihood function. However, this can be rather difficult and time-consuming, particularly when dealing with the three-parameter distribution. Another method of finding the parameter estimates involves taking the partial derivatives of the likelihood equation with respect to the parameters, setting the resulting equations equal to zero, and solving simultaneously to determine the values of the parameter estimates. The log-likelihood functions and associated partial derivatives used to determine maximum likelihood estimates for the lognormal distribution are covered in Appendix C.