Least Squares/Maximum Likelihood Methods for the Decision-Aided GFSK Receiver

2009 ◽  
Vol 16 (6) ◽  
pp. 517-520 ◽  
Author(s):  
Dah-Chung Chang
Keyword(s):  
Maximum Likelihood ◽  
Least Squares ◽  
Likelihood Methods ◽  
Maximum Likelihood Methods

Genetic and environmental effects on milk yield of Pitangueiras cattle

1984 ◽  
Vol 39 (2) ◽  
pp. 157-163 ◽  
Author(s):  
R. B. Lôbo ◽  
F. A. M. Duarte ◽  
A. A. M. Gonçalves ◽  
J. A. Oliveira ◽  
C. J. Wilcox
Keyword(s):  
Maximum Likelihood ◽  
Least Squares ◽  
Milk Yield ◽  
Environmental Effects ◽  
Intraclass Correlation ◽  
Statistical Analyses ◽  
Likelihood Methods ◽  
Maximum Production ◽  
Lactation Length ◽  
Maximum Likelihood Methods

ABSTRACTData from 5270 lactation records of 1380 cows sired by 132 bulls and recorded from 1962 to 1977 were analysed. Statistical analyses, using least squares and maximum likelihood methods, showed significant effects for genetic group, age of cow, month and year of calving, and lactation length. Overall mean milk yield was 2780 kg (CV = 0·31) with mean lactation length of 281 days. Maximum production occurred in the fifth lactation (104 or 105 months of age at calving) with a yield of 1·3 times that of the first lactation. Repeatability estimated by intraclass correlation was 0·40 (s.e. 0·03). Heritability estimated from paternal half-sib correlation was 0·16 (s.e. 0·06). Overall results were very similar to those obtained from research with European breeds in temperate areas.

A comparison of least squares and maximum likelihood methods using sine fitting in ADC testing

Measurement ◽  
2013 ◽  
Vol 46 (10) ◽  
pp. 4362-4368 ◽  
Author(s):  
Ján Šaliga ◽  
István Kollár ◽  
Linus Michaeli ◽  
Ján Buša ◽  
Jozef Lipták ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Least Squares ◽  
Likelihood Methods ◽  
Maximum Likelihood Methods ◽  
Fitting In ◽  
Adc Testing

scholarly journals Selecting between causal and noncausal models with quantile autoregressions

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Alain Hecq ◽  
Li Sun
Keyword(s):  
Time Series ◽  
Maximum Likelihood ◽  
Latin American ◽  
Financial Time Series ◽  
Selection Criterion ◽  
Likelihood Methods ◽  
Approximate Maximum Likelihood ◽  
Financial Time ◽  
Maximum Likelihood Methods ◽  
Latin American Countries

AbstractWe propose a model selection criterion to detect purely causal from purely noncausal models in the framework of quantile autoregressions (QAR). We also present asymptotics for the i.i.d. case with regularly varying distributed innovations in QAR. This new modelling perspective is appealing for investigating the presence of bubbles in economic and financial time series, and is an alternative to approximate maximum likelihood methods. We illustrate our analysis using hyperinflation episodes of Latin American countries.

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