Fitting nonlinear regression model

I have 5 input variables organized in a table:

dt, sinday, cosday, sinhour, coshour

The dependent variable is Q (number of observations).

I wrote the following script:

tbl = table(dt,sinhour,coshour,sinday,cosday);
beta0 = [0;0;0;0;0;0];
modelfun = @(b,x) b(1) + b(2)*dt + b(3)*sinhour + b(4)*coshour + b(5)*sinday + b(6)*cosday;
md1 = fitnlm(tbl,Q,modelfun,beta0);

But it is giving the following error message while running:

Error using internal.stats.parseArgs (line 42)
Wrong number of arguments.

Error in NonLinearModel.fit (line 1379)
            [coefNames,predictorVars,responseVar,weights, ...

Error in fitnlm (line 94)
model = NonLinearModel.fit(X,varargin{:});  

Error in nlmfitoccu (line 57)
md1 = fitnlm(tbl,Q,modelfun,beta0);

I am not been able to sort it out.

Answer 1

[Star Strider]

Two observations:

1. ‘Q’ is not defined, and does not appear to be necessary in your argument list in any event;
2. Your regression is actually linear, so you could use the regress or fitlm functions to get the parameters and statistics.