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Are Logistic growth models more realistic than exponential growth models?
Wiki User
∙ 11y ago
yes because once there is too many of one species the will battle for food which will becoome scarce. pluss not every year has the same climet, like summer might be cooler one year and hotter the next
Wiki User
∙ 11y ago
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What is the use of the Gamma distribution?
It is very frequently used in statistics. First of all, multiplying a Chi-square random variable by a constant you obtain a Gamma random variable. So, for example, most estimates of variance obtained in inferential statistics have a Gamma distribution. The Gamma distribution can also be obtained by summing exponential random variables. So, the Gamma distribution pops out in models where the exponential distribution is used (e.g. reliability, credit risk). It is also used for Internet traffic modeling. See the StatLect entry (link below) for an introduction.
What are the advantages and disadvantages of using scientific models?
disadvantages *not to scale *there are limitations
What are the differences between qualitative and quantitative models?
distinguish between qualitative and quantitative model
Which of the following types of models is generally used to predict long term events?
computer
What’s the difference between a generative and discriminative model?
A generative model will learn categories of data while a discriminative model will simply learn the distinction between different categories of data. Discriminative models will generally outperform generative models on classification tasks.
What are the two major types of population models?
exponential growth and logistic growth
How do you fill the selected cells with the successive months of the year?
Try the logistic function. It models the population growth.
What is binary logistic regression?
Binary logistic regression is a statistical method used to model the relationship between a categorical dependent variable with two levels and one or more independent variables. It estimates the probability that an observation belongs to one of the two categories based on the values of the independent variables. The output is in the form of odds ratios, which describe the influence of the independent variables on the probability of the outcome.
What has the author Douglas R Miller written?
Douglas R. Miller has written: 'Statistical modelling of software reliability' -- subject(s): Computer software, Reliability 'Exponential order statistic models of software reliability growth' -- subject(s): Computer programs, Computer software, Distribution (Probability theory), Exponential functions, Mathematical models, Monotonic functions, Order statistics, Poisson processes, Probability theory, Reliability 'Sole Ownership'
How does Logistic regression Work?
The logistic regression "Supervised machine learning" algorithm can be used to forecast the likelihood of a specific class or occurrence. It is used when the result is binary or dichotomous, and the data can be separated linearly. Logistic regression is usually used to solve problems involving classification models. For more information, Pls visit the 1stepgrow website.
What has the author Roza Sjamsoe'oed written?
Roza Sjamsoe'oed has written: 'The use of logistic regression for developing habitat association models' -- subject(s): Regression analysis, Mathematical models, Habitat (Ecology)
What are the advantages and disadvantage of logistic regression compared with linear regression analysis?
It all depends on what data set you're working with. There a quite a number of different regression analysis models that range the gambit of all functions you can think of. Obviously some are more useful than others. Logistic regression is extremely useful for population modelling because population growth follows a logistic curve. The final goal for any regression analysis is to have a mathematical function that most closely fits your data, so advantages and disadvantages depend entirely upon that.
What is A model that is used in science?
the models of science are idea,computer,realistic,and psychical model :)
What are the three urban growth models?
The three urban growth models are the concentric zone model, the sector model, and the multiple nuclei model. These models describe different patterns of urban development and how cities evolve over time.
What is the similarity between computer models and physical models?
They are both models, andthey both can be explained.
What has the author R Lee Kennedy written?
R. Lee Kennedy has written: 'A comparison of logistic regression and artificial neural network models for the early diagnosis of acute myocardialinfarction (AMI)'
What has the author John A Scrivani written?
John A. Scrivani has written: 'Nonlinear models of height growth for Douglas-fir in southwestern Oregon' -- subject(s): Mathematical models, Growth, Douglas fir
