Maximum likelihood estimates of the parameters of a mixture of two regression lines
- 1 January 1974
- journal article
- research article
- Published by Taylor & Francis in Communications in Statistics
- Vol. 3 (10) , 995-1006
- https://doi.org/10.1080/03610927408827201
Abstract
The method of maximum likelihood is used to estimate the parameters of a mixture of two regression lines, The results of a small simulation study show that when the sample size exceeds 250 and the regression lines are more than three standard deviations apart for at least one half of the data, the maximum likelihood estimates are reliable. When this is net the case their sampling variances are so large that the estimates may not be reliable.Keywords
This publication has 9 references indexed in Scilit:
- On mle of the parameters of a mixture of two normal distributions when the sample size is smallCommunications in Statistics, 1973
- A comparison of some methods for estimating mixed normal distributionsBiometrika, 1972
- Some Comparisons of the Method of Moments and the Method of Maximum Likelihood in Estimating Parameters of a Mixture of Two Normal DensitiesJournal of the American Statistical Association, 1972
- A New Approach to Estimating Switching RegressionsJournal of the American Statistical Association, 1972
- PATTERN CLUSTERING BY MULTIVARIATE MIXTURE ANALYSISMultivariate Behavioral Research, 1970
- Estimation of Finite Mixtures of Distributions from the Exponential FamilyJournal of the American Statistical Association, 1969
- Estimating the components of a mixture of normal distributionsBiometrika, 1969
- Estimation in Mixtures of Two Normal DistributionsTechnometrics, 1967
- Estimation of Parameters for a Mixture of Normal DistributionsTechnometrics, 1966