jcquiroz

jcquiroz

library(shiny)
library(datasets)

# We tweak the "am" field to have nicer factor labels. Since this doesn't
# rely on any user inputs we can do this once at startup and then use the
# value throughout the lifetime of the application
mpgData <- mtcars
mpgData$am <- factor(mpgData$am, labels = c("Automatic", "Manual"))

# Define server logic required to plot various variables against mpg

jcquiroz

list(structure(list(Ft = c(0.00828443, 0.142537, 0.205784, 0.19026, 
0.225401, 0.295057, 0.224034, 0.227109, 0.19411, 0.261652, 0.261515, 
0.28181, 0.319932, 0.261043, 0.221416, 0.30204, 0.189705, 0.229262, 
0.20576, 0.189241, 0.182041, 0.16062, 0.198323, 0.19972, 0.119569, 
0.13151, 0.154239, 0.176638, 0.174014, 0.202141, 0.217325, 0.232339, 
0.249338), SB = c(398628, 372411, 327064, 299841, 278429, 254561, 
268407, 256049, 248592, 261639, 224616, 199638, 161313, 165024, 
137836, 115116, 113422, 107876, 132227, 126253, 135821, 124534, 
128808, 117339, 95778.5, 129940, 124759, 116870, 108635, 100149, 
92081.8, 86251.3, 83672.8), yr = 1978:2010), .Names = c("Ft", 

jcquiroz

kobePlot <- function(dta, v, saveF = TRUE,...)
  {
    F20 <- v[1]
    F40 <- v[2]
    F40.F20 <- F40/F20
    So  <- v[3]
    xxmax <- 1.4*max(dta$Ft,F40.F20)

    kobe <- ggplot(dta, aes(x = Ft/v[1], y = SB/v[3])) +
        theme_bw() + scale_y_continuous(limits=c(0,1)) +

jcquiroz

# nobs
10
# data
1       1.2     0.2
2       3.4     0.2
3       5.1     0.2
4       4.5     0.2
5       7.5     0.2
6       9.3     0.2
7       10.1    0.2

jcquiroz

#include <admodel.h>

 //=================================================================================  
 // Likelihoods for abundance indices or catch
 //=================================================================================  

 dvar_vector nlikelihood(dvector observed, dvar_vector expected, dvector cv, int LikeType)
    {
      RETURN_ARRAYS_INCREMENT();
        dvar_vector logLike;

jcquiroz

GLOBALS_SECTION  
 #include <likelihoodStats.cxx>

DATA_SECTION
 init_int nobs
 init_matrix data(1,nobs,1,3)

PARAMETER_SECTION
 init_bounded_number a(-0.5,0.5,1)
 init_bounded_number b(0.1,3,1)

jcquiroz

structure(list(nobs = 12, data = structure(list(x = c(2.3, 6.7, 
7.5, 3.1, 4.6, 3.9, 8.7, 9.8, 10.1, 6.5, 7.3, 5.2), y = c(5, 
13, 10, 5, 9, 8, 15, 20, 18, 13, 12, 9)), row.names = c(NA, -12L
), .Names = c("x", "y"), class = "data.frame")), .Names = c("nobs", 
"data"))

jcquiroz

library(ggplot2)
library(reshape)

p <- ggplot(subset(reclas))
p1 <- p + geom_bar(aes(factor(length), obs), stat = "identity") 
p2 <- p1 + facet_wrap(~year)
p3 <- p2 + geom_line(aes(factor(length), pre, group = 1))
p4 <- p3 + opts(axis.text.x = theme_text(hjust = 0))
p4