In population biology and demography, generation time is the average time between two consecutive generations in the lineages of a population. In human populations, generation time typically has ranged from 20 to 30 years, with wide variation based on gender and society. [1] [2] Historians sometimes use this to date events, by converting generations into years to obtain rough estimates of time.
The existing definitions of generation time fall into two categories: those that treat generation time as a renewal time of the population, and those that focus on the distance between individuals of one generation and the next. Below are the three most commonly used definitions: [3] [4]
The net reproductive rate is the number of offspring an individual is expected to produce during its lifetime: means demographic equilibrium. One may then define the generation time as the time it takes for the population to increase by a factor of . For example, in microbiology, a population of cells undergoing exponential growth by mitosis replaces each cell by two daughter cells, so that and is the population doubling time.
If the population grows with exponential growth rate , so the population size at time is given by
then generation time is given by
That is, is such that , i.e. .
This definition is a measure of the distance between generations rather than a renewal time of the population. Since many demographic models are female-based (that is, they only take females into account), this definition is often expressed as a mother-daughter distance (the "average age of mothers at birth of their daughters"). However, it is also possible to define a father-son distance (average age of fathers at the birth of their sons) or not to take sex into account at all in the definition. In age-structured population models, an expression is given by: [3] [4]
where is the growth rate of the population, is the survivorship function (probability that an individual survives to age ) and the maternity function (birth function, age-specific fertility). For matrix population models, there is a general formula: [5]
where is the discrete-time growth rate of the population, is its fertility matrix, its reproductive value (row-vector) and its stable stage distribution (column-vector); the are the elasticities of to the fertilities.
This definition is very similar to the previous one but the population need not be at its stable age distribution. Moreover, it can be computed for different cohorts and thus provides more information about the generation time in the population. This measure is given by: [3] [4]
Indeed, the numerator is the sum of the ages at which a member of the cohort reproduces, and the denominator is R0, the average number of offspring it produces.
In mathematics, the discrete Fourier transform (DFT) converts a finite sequence of equally-spaced samples of a function into a same-length sequence of equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency. The interval at which the DTFT is sampled is the reciprocal of the duration of the input sequence. An inverse DFT (IDFT) is a Fourier series, using the DTFT samples as coefficients of complex sinusoids at the corresponding DTFT frequencies. It has the same sample-values as the original input sequence. The DFT is therefore said to be a frequency domain representation of the original input sequence. If the original sequence spans all the non-zero values of a function, its DTFT is continuous, and the DFT provides discrete samples of one cycle. If the original sequence is one cycle of a periodic function, the DFT provides all the non-zero values of one DTFT cycle.
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In physics, Lagrangian mechanics is a formulation of classical mechanics founded on the stationary-action principle. It was introduced by the Italian-French mathematician and astronomer Joseph-Louis Lagrange in his presentation to the Turin Academy of Science in 1760 culminating in his 1788 grand opus, Mécanique analytique.
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