# LOGL

AcronymDefinition
LOGLLots of Good Luck
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Table 3: Selection Criteria of Optimal VAR Lag Order # of Lag LogL LR AIC SC HQ Panel A: Returns on Spot Prices 0 -5,948.63 19,613.93 18.40 18.42 1 -5,907.29 82.18 17,747.67 18.30 18.48 2 -5,898.50 17.37 17,759.66 18.30 18.44 3 (*) -5,888.17 20.34 17,686.82 (*) 18.29 (*) 18.40 (*) 4 -5,883.47 9.21 17,923.58 18.31 18.58 5 -5,871.85 22.67 17,779.03 18.30 18.63 6 -5,863.79 15.64 17,831.19 18.30 18.70 7 -5,858.81 9.62 18,054.82 18.31 18.77 8 -5,857.39 2.73 18,483.60 18.34 18.86 9 -5,848.09 17.80 18,467.29 18.34 18.92 10 -5,845.24 5.43 18,822.87 18.36 19.00 Panel B.
Different RRM were fitted and on the basis of the logarithm of the likelihood function (logL), AIC and BIC values best model were recognized (Table 1).
Table 6.2 VAR Lag Order Selection Criteria Lag LogL LR FPE 0 -362.7281 NA 4777.565 1 -136.2288 391.7825 0.055020 2 -112.3280 36.17433 * 0.037106 * 3 -95.76586 21.48596 0.039199 Lag AIC SC HQ 0 19.82314 19.99730 19.88454 1 8.444803 9.315569 * 8.751788 2 8.017727 9.585107 8.570302 * 3 7.987344 * 10.25134 8.785507 Source: Authors calculations.
logL is the rate of the natural logarithm of maximum likelihood function, p is the number of the parameters of the model, k is a constant equal to the logarithm of the number of observations (n).
maximize(method=bfgs,iterations=1000, parmset=base+constraint) logl 3 *
By only considering relative likelihoods among a series of reference populations, the logL methods do not estimate genotypic (or haplotypic) likelihoods of test groups relative to those of other similar sized groupings within each population, while the MCMC methods tend towards excessive exclusion of reference populations (see Discussion).
A variavel LogL refere-se a funcao de verossimilhanca, a variavel [lambda] refere-se aos autovalores da matriz [A.sub.1] + [G.sub.1] da representacao vech.
Log(T) = [[alpha].sub.0] + [[alpha].sub.1] (logl) + [[alpha].sub.2] (logm) + [[alpha].sub.3] (logh) + [epsilon] (1)
Ms = 0.92 * LogL + 5.33 (with a correlation coefficient = 0.83) (10)
Error 0.36 15.01 0.27 0.29 Log L = -19.42, AIC = 52.84, SC = 62.88 Notes: LM denotes Lagrange Multiplier; LogL denotes Log likelihood; AIC denotes Akaike info criterion; SC denotes Schwarz criterion, ***, ** and * indicate the significance levels of 1%, 5% and 10%.
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