search for: deriv3

What does it require to run the example on page 263 of Venables/Ripley book using R 1.3.0? I got the following error and I have no clue how to correct it. Thank you very much. (If you reply to the list, please send a copy to me.) > lmix2 <- deriv3( + ~ -log(p*dnorm((x-u1)/s1)/s1 + (1-p)*dnorm((x-u2)/s2)/s2), + c("p", "u1", "s1", "u2", "s2"), + function(x, p, u1, s1, u2, s2) NULL) Error in deriv3.formula(~-log(p * dnorm((x - u1)/s1)/s1 + (1 - p) * dnorm((x - : Function H is not in...

...me lines from S-Plus that work perfectly, and running them on R, I get an unexpected error message: R : Copyright 2002, The R Development Core Team Version 1.4.1 (2002-01-30) > library(MASS) > data <- read.table("/usr/local/data/mcmanus.dat",header=T) > mcmanus.frm <- deriv3(~-log(pnorm((2*D1-1)*(b0+b1*TT+b2*Y+b3*LF+b4*NW+b5*D2))),c("b0","b1","b 2","b3","b4","b5"),function(b0,b1,b2,b3,b4,b5,D1,TT,Y,LF,NW,D2) NULL) Error in deriv3.formula(~-log(pnorm((2 * D1 - 1) * (b0 + b1 * TT + b2 * : Function ^A is not...

Hello: Why is deriv3() functioning differently in R from that in Splus using library(MASS) ? For example deriv3(~(t1*log(t2)+lgamma(t1)+(1-t1)*log(y)+y/t2),c("t1","t2"),function(y,t1,t2)NULL) complains of lgamma. Mervyn

...er table. Currently unsupported mathematical functions of one argument include expm1, log1p, log2, log10, cospi, sinpi, and tanpi. While manual differentiation of these proposed additions is straight-forward, their absence complicates what otherwise could be much simpler, such as using deriv() or deriv3() to generate functions, for example to use as an nls model. Thanks, [[alternative HTML version deleted]]

Dear participants to the list, this is my problem: I want to obtain an expression that represents the second derivative of one function. With "deriv3" (package "stats") it is possible to evaluate the second derivative, but I do not know how I can get the (analytical) expression of this derivative. For example: Suppose that I have a function of this form: f(x,y)=x^3+y^3+(x^2)*(y^2). With "deriv3" I can evaluate the first...

...y~x, da) n0 <- nls(y~A[tr]*x/(B[tr]+x), data=da, start=list(A=c(10,10), B=c(3,3)), trace=TRUE) summary(n0) attr(n0$m$fitted(), "gradient") attr(n0$m$fitted(), "hessian") #------------------------------------------------------------ but I want specify a model using deriv3() function because I use the gradient and hessian of the model fit #------------------------------------------------------------ model <- deriv3(~A*x/(B+x), c("A","B"), function(x, A, B) NULL) n1 <- nls(y~model(x, A, B), data=da, start=list(A=c(10), B=c(3)), tra...

The issue is that without an extensible derivative table or the proposed extensions, it is not possible to automatically produce (without manual modification of the deriv3 output) a function that avoids catastrophic cancellation regardless of the working range. Manual modification is not onerous as a one-time exercise, but can be time consuming when it must be done numerous times, for example when evaluating the impact of different parameterizations on parameter eff...

Hello, I was wondering if the functions deriv3(), deriv() etc. could be extended to handle psigamma() and its special cases (digamma(), trigamma() etc.). From the error message it seems that 'psigamma' needs to be added to the derivatives table. This might be easy since psigamma() has a deriv argument. Additionally, this error message...

...riv(~gamma(x),"x") expression({ .expr1 <- gamma(x) .value <- .expr1 .grad <- array(0, c(length(.value), 1), list(NULL, c("x"))) .grad[, "x"] <- .expr1 * psigamma(x) attr(.value, "gradient") <- .grad .value }) BUT > deriv3(~gamma(x),"x") Error in deriv3.formula(~gamma(x), "x") : Function 'psigamma' is not in the derivatives table What I want is the expression for the second derivative (which I believe is trigamma(x), or psigamma(x,1)), how can I obtain that? Thanks -- View this message...

Hi. Unless I'm misremembering, log, exp, sin, cos, and tan are all handled in deriv3. The functions listed are specially coded slightly more accurate versions but can be substituted with native ones for which deriv/deriv3 will work automatically. I believe that if you write your functions using log(a + 1) instead of log1p(a) or log(x) / log(2) instead of log2(x) deriv3 will work...

Wenyaun Xi <xi@keynes.econ.utah.edu> writes to S-news: > I ran into some problems when I tried to get symbolic derivation by > using a function deriv3(). The expression contains 18 > parameters, of which I want to have an information matrix eventually. I > ran it on my 200MHz Pentium PC with 64meg RAM. Each time I kick out the > job, the S-plus 3.1 for Windows stops after about 2 hour of real time > and suggests that it requires m...

Dear List, I am looking for a possibility to fit a mixture model under R using maximum likelihood estimation. Venables and Ripley describe a solution working under S+ (in MASS, 3. ed., p. 263) which requires the D system function and deriv3. This solution does not seem to be portable to R or at least I do not realise how. Is there anyone who a) knows how one could make the MASS-method run under R? or b) has written an EM-algorithm to fit mixture models in R that I could use? I would be glad to hear from someone. Sincerely, Jo...

...name, val ) } lhs <- as.matrix( eval( as.formula( eqn )[[2]] ) ) rhs <- as.matrix( eval( as.formula( eqn )[[3]] ) ) resid <- crossprod( lhs - rhs ) ## just how does this work... attr( obj, "value" ) <- resid attr( obj, "gradient" ) <- attr( eval( deriv3( eqn, names( parmnames ) ) ), "gradient" ) } res <- nlm( obj, sv2, hessian=T, eqn=supply2, data=kmenta, parmnames=sv2, check.analyticals=T) I haven't been able to get nlm to function as I keep getting the following error message: Error in nlm(obj, sv2, hessian = T, eqn = supply...

...e same combination fails to achieve convergence in R despite starting from the estimates reported in JMP. What can I do? Full story: I am collaborating on a project which presently requires the fit of a seven parameter non-linear function to 874 observations. The function is: freeze.d <- deriv3(~ dbh^b * u^dbh * a1 * smi^a2 * exp(a3*pbal) * (1 + a4*exp(a5*ba)) * cr^a6 * dh5^a7, c("a1","a2","a3","a4","a5","a6","a7","b","u"), function(dbh, smi, pbal, ba, cr, dh5, a1, a2, a3, a4, a5, a6, a7, b, u)...

...(x, base = 3)), "x") : only single-argument calls are supported Error in deriv.formula(~log(x, base = 3), "x") : only single-argument calls are supported Error in deriv.default(expression(log(x, base = 3)), "x") : only single-argument calls are supported Error in deriv3.default(expression(log(x, base = 3)), "x") : only single-argument calls are supported Error in D(expression(abs(x)), "x") : Function 'abs' is not in the derivatives table Error in deriv.formula(~abs(x), "x") : Function 'abs' is not in the derivati...

...==== Example from MASSv3 8.7 ========================================================================= library(MASS) data(geyser) attach(geyser) truehist(waiting, xlim=c(35,110), ymax=0.04, h=5) width.SJ(waiting) wait.dns <- density(waiting, 200, width=10.24) lines(wait.dns, lty=2) lmix2 <- deriv3( ~ -log(p*dnorm((x-u1)/s1)/s1 + (1-p)*dnorm((x-u2)/s2)/s2), c("p", "u1", "s1", "u2", "s2"), function(x, p, u1, s1, u2, s2) NULL) p0 <- c(p=mean(waiting < 70), u1=50, s1=5, u2=80, s2=5) tr.ms <- function(info, theta, grad, scal...

...ay, patient$protein, type="b") My goal is two-fold: firstly, I need to test for periodicity, and secondly, I need to try to predict the temporal location of future peaks. Of course, the peaks might be occurring on unmeasured days. I have been looking at this model: wave.form <- deriv3( ~ sin(2*pi*((day-offset)/period + 0.25)) * amplitude + mean, c("period", "offset", "amplitude", "mean"), function(day, period, offset, amplitude, mean){}) curve(wave.form(x, period=7, offset=2, mean=5, amplitude=4), from=1, to=30) S...

...################################################################# patient <- data.frame( day = c(1, 3, 5, 8, 10, 12, 15, 17, 19, 22, 24, 26), protein = c(5, 3, 10, 7, 2, 8, 25, 22, 7, 10, 12, 5) ) plot(patient$day, patient$protein, type="b") # This is my model: wave.form <- deriv3( ~ sin(2*pi*((day-offset)/period + 0.25)) * amplitude + mean, c("period", "offset", "amplitude", "mean"), function(day, period, offset, amplitude, mean){}) curve(wave.form(x, period=7, offset=2, mean=5, amplitude=4), from=1, to=...

...: > only single-argument calls are supported > Error in deriv.formula(~log(x, base = 3), "x") : > only single-argument calls are supported > Error in deriv.default(expression(log(x, base = 3)), "x") : > only single-argument calls are supported > Error in deriv3.default(expression(log(x, base = 3)), "x") : > only single-argument calls are supported > Error in D(expression(abs(x)), "x") : > Function 'abs' is not in the derivatives table > Error in deriv.formula(~abs(x), "x") : > Function 'abs...

Are other developers finding R 3.1.3 problematic because vignette building requires pandoc 1.12.3, while Linux Mint 17 / Ubuntu 14.04 have 1.12.2.1? R 3.1.2 seems to work fine. I'd very much like to avoid having to build as large a Linux package as pandoc, which has given me issues outside of R (it leaves out words, sentences or paragraphs when converting Latex to epub in a novel I'm