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    model for an exponential function

    I am struggling with an exponential kind of function (it's stock market so not a function itself). It's the function of bitcoin basically. As you can see it's exponential-like increasing since 2011. Now I don't give this example for price prediction but for genuine interest...
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    Is this matematical problem also related to some statistic predictive model problem?

    For example: calculataing that area could be a different way to predict instead of minimizing the sum of sum of least squares the problem is to calculate the Area here:
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    black scholes equations applied to tennis

    Hello betfair trader here. I ask this question here because here is full of smart guys. Can I model a tennis match or some statistic regarding a tennis player using black scholes equations? I mean: can they come useful when applied in tennis in order to model the...
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    What is lookback lenghts regression?

    what is it and when is used? I have red about this but I don't know when it's used and its purpose. Can someone be so kind to explain me a little bit what is used for?
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    Markov Chain Models in tennis

    If you already know tennis rules you can skip this wall of text and go directly to the end. If you don't know them... well could you read please? It's a simple introduction on how it works. In tennis, each game is won when one player achieves both of two goals: her score 1...
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    What can use to extrapolate a cause-effect relationship between 2 variables?

    Let's assume that I have found a correlation or an association between two variables. How can I find out if there is cause-effect relationship between the 2 variables? question: The difference between an association and a correlation? A strong association automatically...
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    How can they predict the shape of the bell?

    How can they predict the shape of the bell? (distribution of the possible numbers of infections over the days) During this corona virus I have seen many pics of normal distributions which should predict the number of the infections over the days. As predictive model I only know...
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    equilibrium distribution.

    These algorithms create Markov chains such that they have an equilibrium distribution which is proportional to the function given. could you explain me what does this statment mean with equilibrium distribution which is proportional to the function given? With a simple example...
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    Calculating Conditional Probability of Survival

    shouldn't you use cox regression in this case?
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    Should I use cox regression for this purpose?

    Should I be using cox regression for this? I am analyzing the performance of a tennis player. I want to understand how long on average his performance starts to drop during a match. I indicate an optimal performance when the tennis player makes a good number X of aces a number Y of double fouls...
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    what is the drop out problem in Markov chain?

    Can someone please explaine to me what is the drop out problem?
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    Gaussian process and Gaussian regression

    Hello, I have some problem understing the Gaussian regression and the way it works. Could you please explain to me some things? The first thing I don't understand is why this regression does it use the joint/multivariate probability to get new value of the Y? The...
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    Difference between Mann-Kendall and Pearsons Correlation to obtain p-value

    before to make the linear regression why haven't you calculated the pearson index? It would have been wise to calculate the pearson index BEFORE the linear regression
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    How can be used time series in sport?

    Why don't use a regression model instead of time series analisy?
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    How can be used time series in sport?

    Hello, noob here in statistics. How can be time series be useful to sport stats modelling? Let's take as an examplem footbal
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    What is the difference between sample algorithms and algoritms for estimating parameters?

    I have red this in the website: MCMC is a family of sampling algorithms, which means given a distribution, these algorithms return samples according to this distribution. Many problem, bayesian posterior inference for instance, require you compute the posterior distribution P(θ|D), most of...
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    Before to making a regression

    ''However, with large sample size and a larger average counts,'' What do you mean with ''large average counts'' ? sorry not native-english... Can you make an example? Also ''many say around 8 or larger, the Poisson begins to approximate a normal distribution and a linear model can be...
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    Weighted avearge mean

    Hello here is my problem. I am analizying some tennis matches, and I am able to see the highest odd (bookmaker's odd) reached by that tennis player in N-matches (N is number of matches) Then I take all the highest odds reached by that tennis player during his N-matches , and...
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    Before to making a regression

    Hello I want to ask you, before to making a regression should we understand which distribution follow the datas? Let's take an example: if the data have a poisson distribution, then I will run a Poisson regression? If the data follow a gaussian then one should use...
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    Density probability function considering a subinterval which have different probabilities

    Thanks I don't get it what is F(b) and what is F(a)... sorry.... How do I integrate PDF from a to b? Sorry could you make an example? How could I calculate it numerically?