Displaying 11 results from an estimated 11 matches for "ggt".
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ggtt
2012 Jun 25
2
setdiff datframes
...nscript
V7 V8 V9 V10 V11 V12 V13
1 SYNONYMOUS_CODING 704 705 235 V gtA/gtG
rs4685
2 SYNONYMOUS_CODING 3749 3657 1219 V gtA/gtG
rs4685
3 SYNONYMOUS_CODING 2723 2631 877 G ggT/ggC rs788018
4 SYNONYMOUS_CODING 515 423 141 K aaA/aaG rs788023
5 SYNONYMOUS_CODING 365 27 9 P ccC/ccT
rs41284843
6 SYNONYMOUS_CODING 264 27 9 P ccC/ccT
rs41284843
7 SYNONYMOUS_CODING 365 27...
2011 Nov 18
1
Ensuring a matrix to be positive definite, case involving three matrices
Hi,
I would like to know what should I garantee about P and GGt in order to have
F = Z %*% P %*% t(Z) + GGt always as a positive definite matrix.
Being more precise:
I am trying to find minimum likelihood parameters by using the function
'optim' to find the lowest value generated by $LogLik from the function
'fkf' (http://127.0.0.1:27262/libr...
2011 Sep 22
1
Error in as.vector(data) optim() / fkf()
...r of the transition
equation
Zt <- b #array giving the factor of the measurement equation
ct <- a #matrix giving the intercept of the measurement equation
dt <- (diag(m)-expm(-array(c(K_1, 0, 0, K_2), c(2,2))*h))*theta #matrix
giving the intercept of the transition equation
GGt <- array(c(1,0,0,1), c(d,d,n)) #array giving the variance of the
disturbances of the measurement equation
HHt <- array(c(1,0,0,1), c(m,m,n)) #array giving the variance of the
innovations of the transition equation
a0 <- c(0, 0) #vector giving the initial value/estimation of the sta...
2011 Nov 12
1
State space model
...the factor of the transition
equation
Zt <- b #array giving the factor of the measurement equation
ct <- a #matrix giving the intercept of the measurement equation
dt <- as.matrix((diag(m)-explh)%*%c(theta_1, theta_2)) #matrix giving
the intercept of the transition equation
GGt <- array(diag(d), c(d,d,1)) #array giving the variance of the
disturbances of the measurement equation
HHt <- diag(m) #array giving the variance of the innovations of the
transition equation
a0 <- c(0.5, 0.5) #vector giving the initial value/estimation of the
state variable
P0...
2011 Dec 17
0
time-varying parameters kalman filter estimation problem using FKF package
...file found using ?fkf which demonstrates the MLE of an ARMA(2,1) model.
When I attempt to run my R code (given below) I get the following error:
Error in fkf(a0 = sp$a0, P0 = sp$P0, dt = sp$dt, ct = sp$ct, Tt = sp$Tt, :
Some of dim(dt)[2], dim(ct)[2], dim(Tt)[3],
dim(Zt)[3], dim(HHt)[3], dim(GGt)[3] or
dim(yt)[2] is/are neither equal to 1 nor equal to 'n'!
Here is the R code that generated this error
# Fitting time-varying parameter CAPM to BP stock
# let rt denote adjusted daily returns on a stock
# let rmt denote daily returns on the appropriate benchmark e.g. SP500
# rt = alp...
2011 Jul 05
1
Executing a function several time, how to save the output
...,
I try to exceute a function "myfun" that should use as input "input1.csv"
and "input2.csv" .
Then I try to save the output dat33 on a csv file (on per each time I
execute input1..input 2 and so on). So my problem is how to finally obtain
several csv file with "ggt1.csv", "ggt2.csv".
The program creates ggt1.csv but
BUT when runs "myfun" by second time (It is supossed with input2.csv" it
appears:
Warning messages:
1: In if (file == "") file <- stdout() else if (is.character(file)) { :
the condition has length &...
2012 Feb 29
1
codon usage bias
...agc agg agt ata atc atg att caa cac cag
cat
NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
NA
cca ccc ccg cct cga cgc cgg cgt cta ctc ctg ctt gaa gac gag gat gca gcc gcg
gct
NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
NA
gga ggc ggg ggt gta gtc gtg gtt taa tac tag tat tca tcc tcg tct tga tgc tgg
tgt
NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
NA
tta ttc ttg ttt
NA NA NA NA
it's telling me that there are no codons. I'm not sure how to split up the
data or make this work at all.
Any...
2015 Oct 05
0
Best of the best watches.
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ajk pdaw rwudo xbsz earuk hj...
2009 Dec 22
1
Slow survfit -- is there a faster alternative?
Using R 2.10 on Windows:
I have a filtered database of 650k event observations in a data frame
with 20+ variables.
I'd like to be able to quickly generate estimate and plot survival
curves. However the survfit and cph() functions are extremely slow.
As an example: I tried
results.cox<-coxph(Surv(duration, success) ~ start_time + factor1+
factor2+ variable3, data=filteredData) #(took a
2004 Feb 09
0
Returned mail (PR#6561)
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2013 Mar 06
12
if dentro de for
Buenas,
Me encuentro con el mismo problema, de que me dice que el argumento del if
no es un "valor ausente donde TRUE/FALSE es necesario"
Este es mi codigo de pruebas.
readseq <- "aaaaaaaaaaa", "aaa", "aa")
auxiliar <- count(readseq[j],i+2)
aux_a <- auxiliar["listaa"]
if(aux_a > 0){
matrizgraf3[i][k] = matrizgraf3[i][k] + 1
listaa