Sentences with phrase «kurtosis for»

You get a VERY different result if you even use a lognormal prior with a standard deviation of 0.65 - 0.85 (which maximizes width / Kurtosis for a given mean).

Not exact matches

For that, the researchers rely on something called the kurtosis of a distribution, which measures the size of its tails, or the rate at which the concentration of data decreases far from the mean.

I think there's normally a little more premium in put - selling due to kurtosis (put buyers are willing to pay more for downside protection than call buyers speculating on upside).

Kurtosis, fatter tails and higher peaks, or skewness on the distribution can be problematic for the ratio, as standard deviation doesn't have the same effectiveness when these problems exist.

In particular a more thorough analysis would pay close attention to the kurtosis of the distribution (i.e., the «fatness» of the distribution's tails) and would perhaps model it through a Generalized Pareto Distribution as is done in Otto et al., 2012 for example.

If Monte Carlo analysis were done on the climate models, I am sure that what we would see is pretty much equal probability for any outcome — ie flat kurtosis.

All scales met skewness and kurtosis criteria for normal distribution.

Subsequently, FR - EXT scores were computed by filling in the following regression equation: FR - EXT for externalizing behaviors = SAD mother + SAD father + ASB mother + ASB father, FR - EXT ranged from 0 to 8 (skewness 3.78, kurtosis, 17.63).

All variables demonstrated acceptable levels of skewness and kurtosis with the exception of suicide ideation, which was transformed using the log - likelihood method to correct for non-normality.

Using the cutoffs of two and seven for skew and kurtosis, respectively (West, Finch, & Curran, 1995), all variables were normally distributed.

Kurtosis scores ranged from -0.33 (Distraction) to 0.28 (Forgetting) for the adaptive strategies and from -0.06 (Rumination) to 0.12 (Aggressive Actions) for the maladaptive strategies.

Frequencies for all the independent and dependent variables were examined to ensure normality in terms of skewedness and kurtosis.

As the scores for skewness and kurtosis are between +1 and − 1 for each scale, the distribution can be treated as normal [41].