How to store outputs from Monte Carlo simulation and then calculate probability distribution function?

Hello,

I am beginner with MATLAB so i might have stupid doubts or lack very basic knowledge because this is my first time using matlab.

I need to run MC simulation (1000 times) and store the values of RL_1 , RL_2, and RL_3 (1000 of each) and then based on these values i need to calculate the probability distribution function for each of them, any help?

Here is my code:

clear, close all

freq=csvread('freq.csv',0,0,'A1..A11');

freq1 = freq.';

freqchoose = 31.5;

a = 25;

zero = 0;

distance =1:1:25;

distance=distance';

number_of_runs = 1;

Grids1=readtable('SL_S1.csv'); % Read Source level calculated on excel;

Grids2=readtable('SL_S2.csv'); % Read Source level calculated on excel;

Grids3=readtable('SL_S3.csv'); % Read Source level calculated on excel;

u1 = unique(Grids1.id);

u2 = unique(Grids2.id);

u3 = unique(Grids3.id);

for n = 1:number_of_runs %Monte Carlo simualtion

%----------------------------------------------------------------------------------------------------

%SL values per grid cell for all seasons

for k = 1:numel(u1)

Grids_season1{k} = Grids1{Grids1.id==u1(k),:}; %Extract submatrices season 1 (per grid cell) from SL_PDF matrix

end

for m = 1:numel(u2)

Grids_season2{m} = Grids2{Grids2.id==u2(m),:}; %Extract submatrices season 2 (per grid cell) from SL_PDF matrix

end

for n = 1:numel(u3)

Grids_season3{n} = Grids3{Grids3.id==u3(n),:}; %Extract submatrices season 3 (per grid cell) from SL_PDF matrix

end

%----------------------------------------------------------------------------------------------------

%Random Source Level for season 1

RN = rand(1,100); %Random Number

for RR = 1:length(RN)

ii = find(freq1 == freqchoose); %ii variable is the column number of the freq we chose

if isempty(ii)

disp('error')

return

end

for jj = 1:length(Grids_season1)

SL_freqchoose{jj} = Grids_season1{jj}(:,ii);

[SL_freqchoose_hist{jj},bincenters{jj}] = hist(SL_freqchoose{jj});

PDF{jj}=SL_freqchoose_hist{jj}/length(SL_freqchoose{jj});

BCC{jj} = cumsum(PDF{jj}); %Bincentres Cumulative Sum

if RN(RR)<BCC{jj}

SSL_index{jj} = 1;

else

SSL_index{jj} = find(BCC{jj}<=RN(RR),1,'last');

end

SSL_1{jj} = bincenters{jj}(SSL_index{jj}); %Synthetic Source Level

end

%----------------------------------------------------------------------------------------------------

%The probability distribution of the distance between whale and ship -

%season 1

for jj = 1:length(Grids_season1)

distance_cell{jj}=distance;

pdf{jj}(1:25,1)=1/length(distance); %uniform distribution distance from 0 to 25km

BBC1{jj} = cumsum(pdf{jj});

if RN(RR)<BBC1{jj}

dist_index{jj} = 1;

else

dist_index{jj} = find(BBC1{jj}<=RN(RR),1,'last');

end

dist{jj} = (dist_index{jj}); %Synthetic distance value

Pd{jj} = (2*dist{jj}(1,1)*(-4*dist{jj}(1,1)/(a^3)+pi/(a^2)+dist{jj}(1,1)^2/(a^4)));

TL_1{jj} = 10*log10(Pd{jj});

RL_1{jj} = SSL_1{jj} - TL_1{jj};

end

end

%---------------------------------------------------------------------------------------------------

%Random Source Level for season 2

RN = rand(1,100); %Random Number

for RR = 1:length(RN)

ii = find(freq1 == freqchoose); %ii variable is the column number of the freq we chose

if isempty(ii)

disp('error')

return

end

for jj = 1:length(Grids_season2)

SL_freqchoose{jj} = Grids_season2{jj}(:,ii);

[SL_freqchoose_hist{jj},bincenters{jj}] = hist(SL_freqchoose{jj});

PDF{jj}=SL_freqchoose_hist{jj}/length(SL_freqchoose{jj});

BCC{jj} = cumsum(PDF{jj}); %Bincentres Cumulative Sum

if RN(RR)<BCC{jj}

SSL_index{jj} = 1;

else

SSL_index{jj} = find(BCC{jj}<=RN(RR),1,'last');

end

SSL_2{jj} = bincenters{jj}(SSL_index{jj}); %Synthetic Source Level

end

%---------------------------------------------------------------------------------------------------

%The probability distribution of the distance between whale and ship -

%season 2

for jj = 1:length(Grids_season2)

distance_cell{jj}=distance;

pdf{jj}(1:25,1)=1/length(distance); %uniform distribution distance from 0 to 25km

BBC1{jj} = cumsum(pdf{jj});

if RN(RR)<BBC1{jj}

dist_index{jj} = 1;

else

dist_index{jj} = find(BBC1{jj}<=RN(RR),1,'last');

end

dist{jj} = (dist_index{jj}); %Synthetic distance value

Pd{jj} = (2*dist{jj}(1,1)*(-4*dist{jj}(1,1)/(a^3)+pi/(a^2)+dist{jj}(1,1)^2/(a^4)));

TL_2{jj} = 10*log10(Pd{jj});

RL_2{jj} = SSL_2{jj} - TL_2{jj};

end

end

%---------------------------------------------------------------------------------------------------

%Random Source Level for season 3

RN = rand(1,100); %Random Number

for RR = 1:length(RN)

ii = find(freq1 == freqchoose); %ii variable is the column number of the freq we chose

if isempty(ii)

disp('error')

return

end

for jj = 1:length(Grids_season3)

SL_freqchoose{jj} = Grids_season3{jj}(:,ii);

[SL_freqchoose_hist{jj},bincenters{jj}] = hist(SL_freqchoose{jj});

PDF{jj}=SL_freqchoose_hist{jj}/length(SL_freqchoose{jj});

BCC{jj} = cumsum(PDF{jj}); %Bincentres Cumulative Sum

if RN(RR)<BCC{jj}

SSL_index{jj} = 1;

else

SSL_index{jj} = find(BCC{jj}<=RN(RR),1,'last');

end

SSL_3{jj} = bincenters{jj}(SSL_index{jj}); %Synthetic Source Level

end

end

%------------------------------------------------------------------------------------------------------

%The probability distribution of the distance between whale and ship -

%season 3

for jj = 1:length(Grids_season3)

distance_cell{jj}=distance;

pdf{jj}(1:25,1)=1/length(distance); %uniform distribution distance from 0 to 25km

BBC1{jj} = cumsum(pdf{jj});

if RN(RR)<BBC1{jj}

dist_index{jj} = 1;

else

dist_index{jj} = find(BBC1{jj}<=RN(RR),1,'last');

end

dist{jj} = (dist_index{jj}); %Synthetic distance value

Pd{jj} = (2*dist{jj}(1,1)*(-4*dist{jj}(1,1)/(a^3)+pi/(a^2)+dist{jj}(1,1)^2/(a^4)));

TL_3{jj} = 10*log10(Pd{jj});

RL_3{jj} = SSL_3{jj} - TL_3{jj};

end

end