Sentences with word «kurtosis»

In both study groups, skewness and kurtosis of internalizing and externalizing problem behavior was between − 1 and 1.

Robust test statistics were used to account for non-normality in the data (i.e., positive skew in scores on depressive symptoms and victimization; slight negative kurtosis on relationship dissatisfaction for women).

A large kurtosis for exercise minutes led to creation of a logged exercise minutes variable that was used in subsequent analyses.

You can go one further and use kurtosis — the 4th moment, which gives a relative measure of the proportion of the distribution in the peak to in its tails.

Again, there are multiple ways to infer kurtosis from data samples, and selecting the right one is central to the algorithm's efficiency.

Comparison of Diffusion Metrics Obtained at 1.5 T and 3T in Human Brain With Diffusional Kurtosis Imaging.

Classifying covered calls a «flawed» alternative investment, Mr. Swedroe notes that the strategy has two undesirable traits: (1) The returns exhibit negative skewness (Skewness is a measure of the asymmetry of a distribution) and (2) The strategy eliminates the potential for a highly positive return while having no impact on the potential for an extremely negative return (Kurtosis risk).

Importantly, tail risk — measured by negative skewness and excess kurtosis, statistical representations of the «fat tail» events equity investors know experientially — also trends toward zero with larger allocations to the global macro portfolio.

The distribution looks like a lognormal with standard deviation of about 0.91 — and that's got a pretty serious kurtosis.

Preliminary analyses were performed to explore normality, linearity and homoscedasticity and the negative kurtosis typically found in measures of life satisfaction and relationship satisfaction were observed.

In addition, item 12, 17, and 22 also showed very high kurtosis (i.e., 26.0, 14.1, and 42.7, respectively).

The multivariate kurtosis estimate was high (Mardia normalized z - statistic = 58.71) rejecting multivariate normality.

All variables produced kurtosis statistics that fell within expected range, between 2.1669 and − 2.1669.

Given the large skewness and kurtosis of three of its items, polychoric ordinal alpha was used to investigate the internal consistency.

I saw a study showing that 1) average IQ has increased by 15 points in the past 50 years and that 2) Asians have the highest median IQ with negative kurtosis to the normal distribution.

They measure portfolio performance conventionally (Sharpe ratio), via effects on portfolio return distribution skewness and kurtosis (as an indicator of tail risk) and with investor utility metrics.

A bell can also have fat tails on both sides and a thinner middle, which is called «kurtosis.»

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.

Normality was verified using the Kurtosis - test.

Sortino ratio, Value - at - Risk, tracking error, kurtosis — who can keep them all straight?

They measure portfolio performance conventionally (Sharpe ratio), via effects on portfolio return distribution skewness and kurtosis (as an indicator of tail risk) and with investor utility metrics.

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).

Specifically, they examine contemporaneous interactions between risk parity performance and each of return - volatility relationship, return volatility clustering and fatness of return distribution tails (kurtosis).

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.

When looking at PDFs that seem more - or - less - normal, it would be really nice to compute mean, S.D., skew and kurtosis, and maybe do a normality test.

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.