Search results
Results from the WOW.Com Content Network
[2] [3] A final estimate of the spectrum at a given frequency is obtained by averaging the estimates from the periodograms (at the same frequency) derived from non-overlapping portions of the original series. The method is used in physics, engineering, and applied mathematics. Common applications of Bartlett's method are frequency response ...
JMP – visual analysis and statistics package; LIMDEP – comprehensive statistics and econometrics package; LISREL – statistics package used in structural equation modeling; Maple – programming language with statistical features; Mathematica – a software package with statistical particularly ŋ features
The theoretical return period between occurrences is the inverse of the average frequency of occurrence. For example, a 10-year flood has a 1/10 = 0.1 or 10% chance of being exceeded in any one year and a 50-year flood has a 0.02 or 2% chance of being exceeded in any one year.
Cumulative frequency distribution, adapted cumulative probability distribution, and confidence intervals. Cumulative frequency analysis is the analysis of the frequency of occurrence of values of a phenomenon less than a reference value. The phenomenon may be time- or space-dependent. Cumulative frequency is also called frequency of non-exceedance.
The purpose of the method of averaging is to tell us the qualitative behavior of the vector field when we average it over a period of time. It guarantees that the solution y ( t ) {\displaystyle y(t)} approximates x ( t ) {\displaystyle x(t)} for times t = O ( 1 / ε ) . {\displaystyle t={\mathcal {O}}(1/\varepsilon ).}
A frequency distribution shows a summarized grouping of data divided into mutually exclusive classes and the number of occurrences in a class. It is a way of showing unorganized data notably to show results of an election, income of people for a certain region, sales of a product within a certain period, student loan amounts of graduates, etc.
Thus, the mean time between peaks, including the residence time or mean time before the very first peak, is the inverse of the frequency of exceedance N −1 (y max). If the number of peaks exceeding y max grows as a Poisson process, then the probability that at time t there has not yet been any peak exceeding y max is e − N ( y max ) t . [ 6 ]
Magnitudes in the LSSA spectrum depict the contribution of a frequency or period to the variance of the time series. [4] Generally, spectral magnitudes thus defined enable the output's straightforward significance level regime. [25] Alternatively, spectral magnitudes in the Vaníček spectrum can also be expressed in dB. [26]