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How to implement the following procedure using the function Maple Statistics [CrossCorrelation]?  

alias(FFT = DiscreteTransforms[FourierTransform], IFFT = DiscreteTransforms[InverseFourierTransform]);

nd := Statistics:-Sample(Normal(0, 1));

 xcorr := proc (x, y)
local corrLength, c;
corrLength := op(1, x)+op(1, y)-1;
c := IFFT(`~`[`*`](FFT(Vector(corrLength, x, fill = 0), normalization = none), `~`[conjugate](FFT(Vector(corrLength, y, fill = 0...

How to solve this problem:

 style = line option is not executed within the command Statistics [PointPlot].

 But right click on the graph Style / line is obtained as expected. Except that when you run the initial command, Statistics [PointPlot] ... back to the previous graph.

How generate all possible samples of size n = 2 that can be drawn with replacement from this population [0,1,2]?

It occurs to me using these commands.

 restart; with(combinat); choose([0, 0, 1, 1, 2, 2], 2);

        [[0, 0], [0, 1], [0, 2], [1, 1], [1, 2], [2, 2]]

 permute([0, 0, 1, 1, 2, 2], 2);

[[0, 0], [0, 1], [0, 2], [1, 0], [1, 1], [1, 2], [2, 0], [2, 1], [2, 2]]

I decided to convert an old LR question to Maple 15 syntax and update my Maple T.A. questions. I have it working in Maple, but in MTA I get an error: "java.io.IOException: Maple computation error", I've eliminated lines until I found out the error is when I use Fit to solve for the equation. What am I doing wrong?

Thanks, Stephen

I define 8 x values, and calculate 8 y values with random residuals. Then I solve using least squares.

$x1=180;

We have the data
X := Vector([seq(.1*j, j = 0 .. 16), 1.65], datatype = float):
Y := Vector([2.61, 2.62, 2.62, 2.62, 2.63, 2.63, 2.74, 2.98, 3.66,
 5.04, 7.52, 10.74, 12.62, 10.17, 5, 2.64, 11.5, 35.4], datatype = float):
and the model function of x with 5 parameters
F := a*cosh(b*x^c*sin(d*x^e)):
How to fit F to the data  up to the sum of the squared residuals being about 0.001?
Is such good fit possible with Maple at all? It is interesting that Mathcad (not MATLAB...

Hello,

I'm trying to fit a double-diode equation using Maple.  I can get an analytic form of the fitting function in my two variables V and J of the form V(J), but I want J(V), so I'm using fsolve to extract this.  I'm then trying to fit the resulting function to a set of experimental data, but I'm getting an error about writing to an rtable.  I've tested the function, and it gives me a numeric value if I give it numeric inputs.  Is there a way I can fit it?  Code is below:

i want to write a program to simulate a walk of a drunken sailor who walks out of a bar at the centre of a city. the city has a regular pattern of 24\24 square blocks. the sailor doesnt know where he is going and how to exist teh city. the question is how many blocks will he have to walk to exit the city?

let him start at the centre of the city and assume that he exists the city when he reaches either north, east, south or western borders. it can happen that he wlks...

scatter2d  quantile2 scatter1d is removed?

with(stats): with(statplots): with(transform):
with(random): with(describe): with(plots):
datax:=[normald[5,1](100)]:
datay:=[normald[7,3](100)]:
scatter2d(datax,datay);
quantile2(datax,datay);
scatter1d(datax);
scatter1d[jittered](datax);

who(things) replace it?

Hi everyone,

I want to create a Gaussian PDF so I need to calculate Determinant(sigma) with sigma the covariance matrix of a gaussian variable.

If we call this variable alpha (which is a 12 dimension vector and represents the noise in a discrete dynamical equation), then sigma_ij=ExpectedValue(alpha_i*alpha_j)-ExpectedValue(alpha_i)*ExpectedValue(alpha_j)

and this is zero most of the time! So the covariance matrix is singular and the determinant is zero. 

I am trying to compute the diffusion coefficient from the diffusion equation. I can compute the analytical solution and evaluate it for the parameters I know and for the known time t to get this function:

f:=x->
646.0548255+(309.8026777+568.8289152*I)*((.8781989023+.4782956073*I)*ln(1.+(-.8781989023+I*((-1)*.4782956073))*exp(10000000*((-1)*9.013850411)*Dif+(61.46924721*I)*x))+(.8781989023+.4782956073*I)*ln(1.+(-.8781989023+I*((-1)*.4782956073...

I'm trying to approximate points with a function of certain form with Statistics[NonlinearFit]. I expect the graph in the second example to be closely approximate of the points, just like the first graph. For some reason, the second graph is way off. Seems like a bug. Any suggestions are highly appreciated.

Here is the code

plotApprox := proc(listName)
    local X, Y, convModel, modList;

This is one of rank tests.
Non-parametric methods are widely used for studying populations that take on a ranked order (such as movie reviews receiving one to four stars).
The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences.
In terms of levels of measurement, non-parametric methods result in "ordinal" data.
After the introduction to the topic let's turn to an example.

I have always thought that regressions has been too complicated in Maple. 
The Fit command is too fiddly ie you have to specify too many things and 
it is easy to get it wrong plus the statistical output you get is far from 
mainstream ie you dont get t-values, p-values, R, R^2, Adj R^2 etc etc.

I have therefore designed a module called SReg with a new procedure called Reg()
which only needs one input and that is a datamatrix. It is important however that 

Dear,

I (used Maple12) tried to find the PDF(Y,y) when Y= tan(X) or Y= sin(X) but those cases give FAIL or wrong result

===============================

restart; with(Statistics):
X:= RandomVariable(Uniform(-Pi/4,Pi/4)):

PDF(2*X+1,y) ## work well

but: 

PDF(tan(X),y); # failed
                        ...

Dear,

======================== This code will give error ============

restart;

with(Statistics);

i:=1:

RandomVariable(ProbabilityTable([1/2,1/2]));

=========================

I  used Maple12 and had a hard time debugging my code to find the error . Finally, I found that when we assign the name i a value, then the RandomVariable(ProbabilityTable([...]) will give error message below:

Error, (in Statistics:-Distribution...