This is probably a silly question, but...

given 

GST := AE+AI-ANB-AR-CP

how do i append [i] to each element of the list so I get

AE[i]+AI[i]-ANB[i]-AR[i]-CP[i]

this nearly gets it

(GST@`[]`)~(i);
 

I an unable to get a numerical result out of this triple integral.  Maple runs forever.  I stopped it after about half an hour:

Int(exp(-a^2-b^2-c^2),
    a=b^2/(4*c)..infinity, b=-infinity..infinity, c=0..infinity);
value(%);
evalf(%);

Is there a trick to make it work?

I am working on a project in dynamical system and I am to apply Pontryagins maximum principle of control. i have coded the control equations but it shows an error message "Error, (in dsolve/numeric/bvp/convertsys) too few boundary conditions: expected 7, got 6". What could be the possible problem?

Not sure why I need to invoke the simplify command here, shouldn't the immediate simplification occur?

simplify(%)
                   

However, it does work algebraically

hi.

According to the fhgure attaceh how i can gain the equation (2-27) . I write the equation (2-26) in maple but I couldnot to gain that result.

If possible to reach equation via maple?

Thanks

diff.mw
 

Download diff.mw

The procedure presented here does independence tests of a contingency table by four methods:

1. Pearson's chi-squared (equivalent to Statistics:-ChiSquareIndependenceTest),
2. Yates's continuity correction to Pearson's,
3. G-chi-squared,
4. Fisher's exact.

(All of these have Wikipedia pages. Links are given in the code below.) All computations are done in exact arithmetic. The coup de grace is Fisher's. The first three tests are relatively easy computations and give approximations to the p-value (the probability that the categories are independent), but Fisher's exact test, as its name says, computes it exactly. This requires the generation of all matrices of nonnegative integers that have the same row and column sums as the input matrix, and for each of these matrices computing the product of the factorials of its entries. So, there are relatively few implementations of it, and perhaps none that do it exactly. (Could some with access check Mathematica please?)

Our own Joe Riel's amazing and fast Iterator package makes this computation considerably easier and faster than it otherwise would've been, and I also found inspiration in his example of recursively counting contingency tables found at ?Iterator,BoundedComposition. 

ContingencyTableTests:= proc(
   O::Matrix(nonnegint), #contingency table of observed counts 
   {method::identical(Pearson, Yates, G, Fisher):= 'Pearson'}
)
description 
   "Returns p-value for Pearson's (w/ or w/o Yates's continuity correction)" 
   " or G chi-squared or Fisher's exact test."
   " All computations are done in exact arithmetic."
;
option
   author= "Carl Love <carl.j.love@gmail.com>, 27-Oct-2018",
   references= (                                                           #Ref #s:
      "https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test",         #*1
      "https://en.wikipedia.org/wiki/Yates%27s_correction_for_continuity",  #*2
      "https://en.wikipedia.org/wiki/G-test",                               #*3
      "https://en.wikipedia.org/wiki/Fisher%27s_exact_test",                #*4
      "Eric W Weisstein \"Fisher's Exact Test\" _MathWorld_--A Wolfram web resource:"
      " http://mathworld.wolfram.com/FishersExactTest.html"                 #*5
   )
;
uses AT= ArrayTools, St= Statistics, It= Iterator;
local
   #column & row sums: 
   C:= AT:-AddAlongDimension(O,1), R:= AT:-AddAlongDimension(O,2),
   r:= numelems(R), c:= numelems(C), #counts of rows & columns
   n:= add(R), #number of observations
   #matrix of expected values under null hypothesis (independence):
   #(A 0 entry would mean a 0 row or column in the original, which is not allowed.)
   E:= Matrix((r,c), (i,j)-> R[i]*C[j], datatype= 'positive') / n,
   #Pearson's, Yates's, and G all use a chi-sq statistic, each computed by 
   #slightly different formulae.
   Chi2:= add@~table([
       'Pearson'= (O-> (O-E)^~2 /~ E),                     #see *1
       'Yates'= (O-> (abs~(O - E) -~ 1/2)^~2 /~ E),        #see *2
       'G'= (O-> 2*O*~map(x-> `if`(x=0, 0, ln(x)), O/~E))  #see *3
   ]), 
   row, #alternative rows generated for Fisher's
   Cutoff:= mul(O!~), #cut-off value for less likely matrices
   #Generate recursively all contingency tables whose row and column sums match O.
   #Compute their probabilities under independence. Sum probabilities of all those
   #at most as probable as O. (see *5, *4)
   #Parameters: 
   #   C = column sums remaining to be filled; 
   #   F = product of factorials of entries of contingency table being built;
   #   i = row to be chosen this iteration
   AllCTs:= (C, F, i)->
      if i = r then #Recursion ends; last row is C, the unused portion of column sums. 
         (P-> `if`(P >= Cutoff, 1/P, 0))(F*mul(C!~))
      else
         add(
            thisproc(C - row[], F*mul(row[]!~), i+1), 
            row= It:-BoundedComposition(C, R[i])
         )
      fi      
;
   userinfo(1, ContingencyTableTests, "Table of expected values:", print(E));
   if method = 'Fisher' then AllCTs(C, 1, 1)*mul(R!~)*mul(C!~)/n!
   else 1 - St:-CDF(ChiSquare((r-1)*(c-1)), Chi2[method](O)) 
   fi   
end proc:

The worksheet below contains the code above and one problem solved by the 4 methods

Download FishersExact.mw

Here's a slightly reduced form of a little module from some code that I posted recently:

KandR:= module()
local
   a, b, c, e, #parameters

   #procedure that lets user set parameter values:
   ModuleApply:= proc({
       a::algebraic:= KandR:-a, b::algebraic:= KandR:-b, 
       c::algebraic:= KandR:-c, e::algebraic:= KandR:-e
   })
   local k;
      for k to _noptions do thismodule[lhs(_options[k])]:= rhs(_options[k]) od;
      return
   end proc
;
end module:

The purpose of the module is simply to be a container for the four parameters and to provide a simple ModuleApply interface by which they can be set, reset, and/or unset. 

I very often use a procedure parameter of a ModuleApply to set a local variable of same name in the module. Because of the name conflict, thismodule needs to be used in these situations. I see this as the primary use of thismodule. In the module above, the purpose of the line 

for k to _noptions do thismodule[lhs(_options[k])]:= rhs(_options[k]) od;

is to avoid the need to explictly use the parameters yet a third time. First off, I am amazed that this works! I've had many disappointments with thismodule (which is essentially undocumented---its miniscule help page is nearly worthless). I am using Maple 2018, release 1. Another Maple 2018 user (not sure which release) reports that the above line gives an error (when executed) that thismodule's index must be a name.

Question 1: What's up with that?

[Edit: It's been determined that the problem was due to an unfortunate global assignment in that user's initialization file rather than different behavior of thismodule. So, I consider Question 1 to be completely answered, and it should be ignored.]

Question 2: The for loop is not entirely satisfying to me. Is there a better way?

[Status: Answered, see below.]

Question 3: Ideally, I'd like to explicity use the four parameters once, not two or three times. Is there a way? If I need to use a container for the parameters (such as a Record), to achieve that, I'd be happy to do that, and I wouldn't mind needing to invoke that container's name any number of times.

[Status: Answered, see below.]

Note that op and exports can be applied to thismodule to extract the module's operands. I have found this occasionally useful.

Question 4: What are some other good uses for thismodule? The one and only example given on its help page seems ridiculous to me.

The docs say that you can assign initial values to a record as shown in this screenshot:

I would expect the last two lines of output to be 1, 2. The slighly more complicated example in the docs does not work as expected either. This is the worksheet: queery.mw

I can assign to a record subsequently, but that makes for very prolix code,

Thanks for any help.

Hello,

I am trying to get Maple to recognize and reverse the product rule in more than one dimension. In one dimension, this works:

Int((Diff(f(x), x))*g(x)+(Diff(g(x), x))*f(x), x) = int((diff(f(x), x))*g(x)+f(x)*(diff(g(x), x)), x);

.

But in two dimensions, it no longer evaluates:

Int((Diff(f(x, y), x))*g(x, y)+(Diff(g(x, y), x))*f(x, y), x) = int((diff(f(x, y), x))*g(x, y)+f(x, y)*(diff(g(x, y), x)), x)

As far as I can tell, mathematically these should be identical (except for the antiderivatives being defined up to a constant in the first case and a function of y in the second). Is there a way to get Maple to reverse the product rule to integrate in more than one dimension? Or am I missing something mathematically that makes this incorrect?

Thanks for your help,

Johnathan

I have asked this before but am still confused. I have a half-dozen procedures I want to save. Don't want them in a module/package. I am using windows 10.

I just can't get the syntax correct on this.

Obviously after saving restart and load to test.

libname;
       "C:\Program Files\Maple 2018\lib", 

         "C:\Users\Ronan\maple\toolbox\CodeBuilder\lib", 

         "C:\Users\Ronan\maple\toolbox\OEIS\lib", 

         "C:\Users\Ronan\maple\toolbox\personal\lib", 

         "C:\Users\Ronan\maple\toolbox\UTF8\lib"
libdir := "C:/Users/Ronan/maple/toolbox/personal/lib";
     libdir := "C:/Users/Ronan/maple/toolbox/personal/lib"
NULL;

LibraryTools:-Save(Pedal, cat(kernelopts(homedir), "/maple/toolbox/personal/lib/Pedal.mpl"));
Error, (in LibraryTools:-Save) could not open `C:\Users\Ronan/maple/toolbox/personal/lib/Pedal.mpl\Pedal.m` for writing

I trying to get a proc to work. In the 1st half of the document, I derive four sections for a pedal curve and plot them fine. In the second I try doing it with a procedure called Pedal. Am having problems. I think it might be something to do with the for.. do loop. 

Download Proc_for_Pedal_not_working.mw

Hi

I am trying to evaluate a function that contains an infinite sum. I need to evaluate the integral to determine a CDF, and from that hopefully the inverse CDF in order to sample the corresponding PDF.

The sum comes from a 2F1 hypergeometric function, which I have written manually in the attached file.

Can anyone tell me if and how it is possible to evaluate this integral, with respect to x?

I have inserted an image below, but also the entire file :) Marginal2.mw

Thanks in advance.

Maple 2018 starts but block and hangs after the first imput.

Even after a clean install on a clean disk where there are no old files of maple.

My specs are: WIN10 pr 64/ I7 /16 GB/ SSD

Who has the same problem and a sollution?

The attached worksheet shows how to evaluate and graphically analyze an autonomous first-order nonlinear recurrence with two dependent variables and multiple symbolic parameters. 

This worksheet shows how a small module that simply encapsulates the given information of a problem combined with some use statements can greatly facilitate the organization of one's work, can encapsulate the setting of parameter values, and can allow one to work with symbolic parameters.

Edit: In the first version of this Post, I forgot to include the qualifier "autonomous".  The system being autonomous substantially simplifies its treatment.
 

Download FoxesAndRabbits.mw

I have a solution to a linear ODE which is very long and complicated.  The solition clearly has some parts which are repeated and so it would would be easiest to express those repeated parts as something simpler.

For example, suppose I had

x = (-b + sqrt(b^2 - 4*a*c) ) /2*a

What is the command to take x and do someting like

Z = sqrt(b^2 - 4*a*c)

x = (-b + Z)/2*a