Cox Proportional Hazard in JuMP.jl - julia

Question

I am trying JuMP.jl in Julia for the first time and can't seem to get around an error. Here is my set up.
using DataFrames, DataFramesMeta, JuMP, Ipopt
#time to event
times = [143,164,188,189,190,192,206,209,213,216,220,227,230,234,246,265,304,216,244,
142,156,163,198,205,232,232,233,233,233,233,239,240,261,280,280,296,296,232,204,344];
#make censored data
is_censored = zeros(Int32, 40);
is_censored[18]=1
is_censored[19]=1
is_censored[39]=1
is_censored[40]=1
#treatment vs control
x1=ones(Int32,19)
x2=zeros(Int32,21)
x=append!(x1,x2)
#build DataFrame
using DataFrames
df = DataFrame();
df[:times]=times;
df[:is_censored]= is_censored;
df[:x]=x;
df
#sort df
df_sorted = sort!(df, cols = [order(:times)])
#make df_risk and df_uncensored
df_uncensored = #where(df_sorted, :is_censored .== 0)
df_risk = df_sorted
#cox partial likelihood
#use JuMP
##convert df to array
uncensored = convert(Array,df_uncensored[:x])
risk_set = convert(Array,df_risk[:x])
m = Model(solver=IpoptSolver(print_level=0))
#variable(m, β, start = 0.0)
#NLobjective(m, Max, sum(uncensored[i]*β-log*sum(exp(risk_set[j]*β) for j=1:length(risk_set)) for i=1:length(uncensored)))
The last line is where all of my problems are
#NLobjective(m, Max, sum(uncensored[i]*β-log*sum(exp(risk_set[j]*β) for j=1:length(risk_set)) for i=1:length(uncensored)))
I get the error
ERROR: MethodError: no method matching parseNLExpr_runtime(::JuMP.Model, ::Base.#log, ::Array{ReverseDiffSparse.NodeData,1}, ::Int64, ::Array{Float64,1})
Closest candidates are:
parseNLExpr_runtime(::JuMP.Model, ::Number, ::Any, ::Any, ::Any) at /home/icarus/.julia/v0.6/JuMP/src/parsenlp.jl:196
parseNLExpr_runtime(::JuMP.Model, ::JuMP.Variable, ::Any, ::Any, ::Any) at /home/icarus/.julia/v0.6/JuMP/src/parsenlp.jl:202
parseNLExpr_runtime(::JuMP.Model, ::JuMP.NonlinearExpression, ::Any, ::Any, ::Any) at /home/icarus/.julia/v0.6/JuMP/src/parsenlp.jl:208
...
Stacktrace:
[1] macro expansion at /home/icarus/.julia/v0.6/JuMP/src/parseExpr_staged.jl:489 [inlined]
[2] macro expansion at /home/icarus/.julia/v0.6/JuMP/src/parsenlp.jl:226 [inlined]
[3] macro expansion at /home/icarus/.julia/v0.6/JuMP/src/macros.jl:1086 [inlined]
[4] anonymous at ./<missing>:?
Examples I have been trying to use as are the maximum likelihood example and the optimal control

Answer 1

You probably meant to write
log(sum(exp(risk_set[j]*β) for j=1:length(risk_set)))
instead of
log*sum(exp(risk_set[j]*β) for j=1:length(risk_set))