Items tagged with poisson


I wish to study the trend of medical consultations each day during six years. Thus I expect near 2200 datas to analyse.

But some parameters are to consider :

- I don't have yet the datas per day, but the mean is about 2 consultations per day

- as it is difficult to do more than 3 or perhaps 4 consultations during one day (9h30 am - 13h pm), the others if they exist will probably be seen the next day (aso if the next day 3 news consultations occured)

- then, I don't know actually (as I expect the datas or each day but don't have now these datas) if the better distribution will be simply follow a Poisson' law, or exponential, or negative binomial, ..

- do someone have a clue for the better law given what i said ?


Further, I don't have a stastic program especially used for time trend, excepting Systran 13, but I don't believe that this program can be used with a theoric model of distribution, I recall that it does usual tasks, autocorrelations, saisonnal adjustments, .. but with continuous distributions I believe, and a linear model (removing the basic frequencies)

As such program (study of temporal series) is usually sold about 3000$ in France, that I don't expect to be a trader, with only one calculus to do, could anyone tell me how to adjust the better model to the 2200 datas that could be expected ?

Thx for your help, friendly yours;



Hi, I'm trying to reproduce the code book Burden Faires (Poisson Equation Finite-Difference. Buden Faires book Numerical Analysis 9th) page 720, algorithm 12.1., But I do not get the exact calculations of Example 2 from page 722. Under the code in maple. Regards.


Comment calculer, sous maple, le crochet de Poisson des deux fonctions suivantes :




Merci d'avance,


I have a bit of an issue.


I'm trying to solve this:

eq1:= exp(-lambda)*exp(k)/factorial(k) > .95



Warning, solutions may have been lost

Dear Maple users

This might have been asked before, I'm asking because I believe the solution to my problem is simpler than what i found on google.

I have this problem:


I wonder how do I show with Maple that for


the series

sum(p(x,a,b),x=0..infinity) assuming a>0,b<1,b>-1

converges to 1. I also tried

sum(a*(a+x*b)^(x-1)*(exp(-(a+x*b)))/(x!), x=m..infinity) assuming a>0,b<1,b>-1,a+m*b<=0

but all to no avail. For b=0, Maple shows the series converges and we have the Poisson distribution. For b in (-1,1), the (discrete) density...

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