similar to: Solving linear equations

Didn't get any useful response to the following question. Trying again. -------------------------------------------------------------------------------- I can't seem to get computationally stable estimates for the following system: Y=a+bX+cX^2+dX^3, where X~N(0,1). (Y is expressed as a linear combination of the first three powers of a standard normal variable.) Assuming that E(Y)=0 and

Hi, I would appreciate if someone could help me on track with this problem. I want to compute some parameters from a system of equations given a number of sample observations. The system looks like this: sum_i( A+b_i>0 & A+b_i>C+d_i) = x sum_i( C+d_i>0 & C+d_i>A+b_i) = y sum_i( exp(E+f_i) * ( A+b_i>0 & A+b_i>C+d_i) = z A, C, E are free variables while the other

I'm about to write my thesis in economics and will need to setup and solve a system of non-linear equations. At our university we usually use GAMS for this, and though GAMS is a fine program, it bugs me a that I won't be able to run my code after I finish my thesis without buying a license for the program(about $3.500 :-(( ) So I've looked around for NL-stuff for R, but I

I have a dataset X Y1 1200 1.375 4000 0.464 1333.33 0.148 444.44 0.047 148.148 0.014 49.383 0.005 16.461 0.004 I have to find a curve fit for the above dataset based on a 4-parameter logistic equation viz. Y1 = d + ((a-d)/(1+(X/cc)^b)), where X and Y1 are the values above. I need to know how to solve the above equation for values a, b, c, d. -- View this message in context:

Offlist, because this is (a) an opinion and (b) about statistics and therefore offtopic. I don't know whether any such package exists, but I would predict that this is likely to be overdetermined (too many parameters) and therefore unlikely to be a successful strategy. Fitting a mixture of Gaussians is already difficult enough. Feel free to ignore, of course, and no need to reply. Cheers,

I don?t see how neither a) or b) applies to this question nor the technical merit of the remark about mixture models. Do you have a suggestion for a more appropriate forum for this issue/question? (stackoverflow basically sent me here). Kind regards > On 29. Jun 2017, at 16:58, Bert Gunter <bgunter.4567 at gmail.com> wrote: > > Offlist, because this is (a) an opinion and (b)

I am trying to write a function that will solve a simple system of nonlinear equations for the parameters that describe the beta distribution (a,b) given the mean and variance. mean = a/(a+b) variance = (a*b)/(((a+b)^2) * (a+b+1)) Any help as to where to start would be welcome. -- Scott Story Graduate Student MSU Ecology Department 319 Lewis Hall Bozeman, Mt 59717 406.994.2670 sstory at

I need to solve a system of non-linear fourth-order differential equations. Is there a command which solves this system? Thanks in advance.

Hello everyone, I have estimated system of three linear equations with one non-linear restrictions with nlsystemfit. I was wondering how I can calculate the R-squared (or some alternative coefficient of determination) for the whole system. This is automatically given by linear systemfit but not by nlsystemfit. I can get the values for each of the equations separately, but apparently not for

Hello Everybody, I am running R 2.2.0 with Windows XP i am trying to fit nonlinear differential equation to data sets which looks like this: Week N C 0 1 1 1 5 6 2 6.2 12.2 3 59 71.2 4 39 110.2 5 38 148.2 6 44 192.2 7 20.4 212.6 8 19.4 232 9 34.2 266.2 10 35.4 301.6 and i need to fit these data to the following diff equation: dNdt=a*N-b*N*C, dCdt=N^2, Where a=birth rate, b=death rate and N=

I have a simple system of linear equations to solve for X, aX=b: > a [,1] [,2] [,3] [,4] [1,] 1 2 1 1 [2,] 3 0 0 4 [3,] 1 -4 -2 -2 [4,] 0 0 0 0 > b [,1] [1,] 0 [2,] 2 [3,] 2 [4,] 0 (This is ex Ch1, 2.2 of Artin, Algebra). So, 3 eqs in 4 unknowns. One can easily use row-reductions to find a homogeneous solution(b=0) of: X_1

Hello R users, I am trying to estimate the parameters of a bimodal normal distribution using moments matching, so I have to solve a non-linear system of equations. How can I solve the following simple example? x^2 - y^2 = 6 x ? y = 3 I heard about nlsystemfit, but I don?t know how to run it exactly. I have tried the following code, but it doesn?t really work: f1 <-y~ x[1]^2-x[2]^2-6 f2

Greetings, In my opinion the documentation or behaviour of qr.solve, qr.coef, qr.resid, and qr.fitted is not easily comprehensible and unfortunate. We all know that a linear system Ax=b can have 0, one or infinitely many solutions. To treat all these cases uniformly we can rephrase the problem as x = argmin_u||Au-b||,

Hi, I have 20*60 data matrix (with some NAs) and I wish to perfom a Pearson correlation coefficient matrix as well as simple linear regression equation and coefficient of determination (R2) for every possible combination. Any tip/idea/library/script how do to so. Thanks, As hz -- View this message in context:

Hi All, I’ve got a question about Module::getOrInsertFunction(). I got an impression that it is not deterministic where exactly in the bit code module the new function will be inserted. Is there a way to make it deterministic by explicitly specifying some offset at which the function should be inserted? Please correct me if I’m wrong. Thank you very much in advance for help, Best regards, Tomek

On 05/29/2014 11:06 AM, Tim Northover wrote: > Hi Tomek, > >> I’ve got a question about Module::getOrInsertFunction(). >> I got an impression that it is not deterministic where exactly in the bit >> code module the new function will be inserted. > Looking at the code (not exhaustively), it seems a new function will > always be added to the end of a module. > >

Hello, I have 8 Samba servers with 300 clients here running on Sun and Linux machines with GREAT performance. Now in one departement i installed samba 2.0.6 on one 40K$ IBM F50 with AIX 4.3.2, 2xCPU, 256MB RAM, 100FDX, extern RAID 5 Tower . Performance is really very, very BAD. I tried already everything, but this IBM box with samba is just very SLOW. Browsing through directories, logging, copying

Hi, I am trying to find a simple way to numerically solve a system of two equations equal to zero with two unknowns (x_loc and y_loc). Here is a mock data set and below it, the equations I need to solve. theta<-c(180,135,90)/(2*pi) x<-c(0,0,15) y<-c(20,0,0) 0 = -sum((y_loc-y)*(sin(theta)*(x_loc-x)-cos(theta)*(y_loc-y))/(((x_loc-x)^2+(y_loc-y)^2)^0.5)^3) 0 =

To R-helpers, R offers the polyroot function for solving mentioned equations iteratively. However, Dr Math and Mathworld (and other places) show in detail how to solve mentioned equations non-iteratively. Do implementations for R that are non-iterative and that solve mentioned equations exists? Regards, Mads Jeppe

Hi, To my knowledge, Ryacas can do symbolic computation in R, like Mathematica or Maple. I wonder if it (or any other R package) can solve symbolically a system of equations? I have a system of four equations in four variables (non-linear, but not very hard to solve) and wonder if Ryacas or any other package can do it. I do not find the solution in Ryacas. Can it find a symbolic solution