scholarly journals Estimation of expected value and coefficient of variation for lognormal and gamma distributions

1978 ◽  
Author(s):  
G.C. White
Keyword(s):  
Coefficient Of Variation ◽  
Expected Value ◽  
Gamma Distributions

Interspike interval distributions of spiking neurons driven by fluctuating inputs

2011 ◽  
Vol 106 (1) ◽  
pp. 361-373 ◽  
Author(s):  
Srdjan Ostojic
Keyword(s):  
Coefficient Of Variation ◽  
Cortical Neurons ◽  
Interspike Interval ◽  
Full Range ◽  
Spiking Neurons ◽  
Neuron Models ◽  
Integrate And Fire ◽  
Gamma Distributions ◽  
Spiking Neuron Models ◽  
Analytical Tools

Interspike interval (ISI) distributions of cortical neurons exhibit a range of different shapes. Wide ISI distributions are believed to stem from a balance of excitatory and inhibitory inputs that leads to a strongly fluctuating total drive. An important question is whether the full range of experimentally observed ISI distributions can be reproduced by modulating this balance. To address this issue, we investigate the shape of the ISI distributions of spiking neuron models receiving fluctuating inputs. Using analytical tools to describe the ISI distribution of a leaky integrate-and-fire (LIF) neuron, we identify three key features: 1) the ISI distribution displays an exponential decay at long ISIs independently of the strength of the fluctuating input; 2) as the amplitude of the input fluctuations is increased, the ISI distribution evolves progressively between three types, a narrow distribution (suprathreshold input), an exponential with an effective refractory period (subthreshold but suprareset input), and a bursting exponential (subreset input); 3) the shape of the ISI distribution is approximately independent of the mean ISI and determined only by the coefficient of variation. Numerical simulations show that these features are not specific to the LIF model but are also present in the ISI distributions of the exponential integrate-and-fire model and a Hodgkin-Huxley-like model. Moreover, we observe that for a fixed mean and coefficient of variation of ISIs, the full ISI distributions of the three models are nearly identical. We conclude that the ISI distributions of spiking neurons in the presence of fluctuating inputs are well described by gamma distributions.

Structural evaluation and strengthening of tall buildings: expected value and coefficient of variation of limit state capacity

2012 ◽  
Vol 21 ◽  
pp. 31-47 ◽  
Author(s):  
Nicolino G. Delli Quadri ◽  
Colin Kumabe ◽  
Ifa Kashefi ◽  
Larry Brugger ◽  
Lauren D. Carpenter ◽  
...  
Keyword(s):  
Coefficient Of Variation ◽  
State Capacity ◽  
Limit State ◽  
Tall Buildings ◽  
Expected Value ◽  
Structural Evaluation

scholarly journals Min And Max Normal Extreme Interval Values And Statistics

2011 ◽  
Vol 6 (8) ◽  
Author(s):  
Marsha Jance ◽  
Nick Thomopoulos
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Expected Value ◽  
Font Size ◽  
Interval Value

<p class="MsoNormal" style="text-align: justify; line-height: normal; margin: 0in 0.5in 0pt;"><span style="font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt;">The method for determining the min and max normal extreme interval values and statistics: expected value, standard deviation, median, mode, and coefficient of variation is discussed.<span style="mso-spacerun: yes;">&nbsp; </span>An extreme interval value </span><span style="font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-theme-font: minor-fareast;"><span style="mso-spacerun: yes;">&nbsp;</span></span><span style="font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt;">is defined as a numerical bound, where a specified percentage &alpha; of the data is less than or equal to ga</span><span style="font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-theme-font: minor-fareast;">.</span></p>

Approximate Confidence Limits for the Coefficient of Variation of Gamma Distributions

Biometrics ◽  
1965 ◽  
Vol 21 (3) ◽  
pp. 733 ◽  
Author(s):  
H. Linhart
Keyword(s):  
Coefficient Of Variation ◽  
Confidence Limits ◽  
Gamma Distributions

scholarly journals Min And Max Uniform Extreme Interval Values And Statistics

2011 ◽  
Vol 7 (1) ◽  
Author(s):  
Marsha Jance ◽  
Nick Thomopoulos
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Expected Value ◽  
Font Size ◽  
Numerical Example ◽  
Relative Line ◽  
Parameter Values ◽  
Uniform Parameter ◽  
Interval Value

<p class="MsoNormal" style="text-align: justify; line-height: normal; margin: 0in 0.5in 0pt;"><span style="font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt;">The min and max uniform extreme interval values and statistics; ie expected value, standard deviation, mode, median, and coefficient of variation, are discussed.<span style="mso-spacerun: yes;">&nbsp;&nbsp; </span>An extreme interval value </span><span style="position: relative; line-height: 115%; font-family: &quot;Calibri&quot;,&quot;sans-serif&quot;; font-size: 11pt; top: 4pt; mso-fareast-font-family: Calibri; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; mso-text-raise: -4.0pt; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;"></span><span style="font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt;">is defined as a numerical bound where a specified percentage &alpha; of the data is less than </span><span style="position: relative; line-height: 115%; font-family: &quot;Calibri&quot;,&quot;sans-serif&quot;; font-size: 11pt; top: 4pt; mso-fareast-font-family: Calibri; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; mso-text-raise: -4.0pt; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;"></span><span style="font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-theme-font: minor-fareast;">. A numerical example and an analysis of the min and max extreme interval values and statistics are provided.<span style="mso-spacerun: yes;">&nbsp; </span>In addition, a procedure for finding the min and max extreme interval values for different uniform parameter values, and an application of this research are presented.</span></p>

scholarly journals Min And Max Exponential Extreme Interval Values And Statistics

2009 ◽  
Vol 2 (1) ◽  
pp. 47-52
Author(s):  
Marsha Jance ◽  
Nick Thomopoulos
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Expected Value ◽  
Sample Sizes ◽  
Interval Value

The extreme interval values and statistics (expected value, median, mode, standard deviation, and coefficient of variation) for the smallest (min) and largest (max) values of exponentially distributed variables with parameter ? = 1 are examined for different observation (sample) sizes. An extreme interval value is defined as a numerical bound where a specified percentage ? of the data is less than . A procedure for finding the extreme interval values when ? > 0, an analysis of the extreme interval values and statistics, and an application of this research are provided.

scholarly journals Analisis Resiko Penangkar Benih Padi Pada Program Desa Mandiri Benih Di Kabupaten Pringsewu

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Dyah Rianita Susanti
Keyword(s):  
Relative Risk ◽  
Standard Deviation ◽  
Data Collection ◽  
Coefficient Of Variation ◽  
Expected Value ◽  
Variation Coefficient ◽  
Rice Seed ◽  
Rice Farming ◽  
Coefficient Method ◽  
Level Of Risk

ABSTRACT The objective of this research was to analyze the risk of rice seed breeder in Pringsewu District. The research was conducted in Pringsewu District. The location was determined purposively, considering that Pringsewu Regency was a rice producing center in Lampung Province. Based on the calculation, the study sample consisted of 37 rice breeders and 37 non-breeders. The data collection of this research was conducted in November 2017. This research employed variation coefficient method to analyze risk. The coefficient of variation (CV) is a measure of the relative risk obtained by dividing the standard deviation by the expected value. The results of the research showed that the level of risk of rice farming in Pringsewu regency for non-paddy breeder farmers was higher than paddy farmer breeders.  

Manipulating the attractiveness of a gamble without changing its expected value.

1969 ◽  
Vol 79 (1, Pt.1) ◽  
pp. 139-145 ◽  
Author(s):  
Paul Slovic
Keyword(s):  
Expected Value

400-P: High Levels of Glycemic Coefficient of Variation Are Associated with Higher Hypoglycemia Episodes in T1D Adults in a Brazilian Tertiary Hospital

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 400-P
Author(s):  
THAIS B. BRASIL ◽  
ANDREI C. SPOSITO ◽  
BEATRIZ ADACHI ◽  
WALKYRIA M. VOLPINI ◽  
ELIZABETH J. PAVIN
Keyword(s):  
Coefficient Of Variation ◽  
Tertiary Hospital
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