Apache Simple Linear Regression In Java using Math Library

I am quite a newbie in using the apache library for a simple linear regress.
Task: I want to calculate the slope.

I have two linear lists, i.e., x-list and y-list. Y list values are the series of number. I am populating x-list by fetching value from a hashmap.

However, when I am trying to apply simpleRegression utility of apache library I am facing below difficulty:

Here is my code:

while(i< segmentI)
                {
                    xList.add(Double.parseDouble(timeStamp.get(i)));
                    yList.add(Double.parseDouble("1"));
                    i++;
                }
                for(int m=0; i< segmentI; i++)
                {
                        simpleRegression.addData(new double[][]{
                                {xList.get(m),yList.get(m)}
                        });

                }

Doubt: Is there any way can I create new double[][] before passing it to simpleRegression.
Also, new double[][]-it is a matrix then what would be the value of [0,1], [0,2]... so on because we don't have anything like that in single ArrayList.

Anything in this regard will be helpful.

> Is there any way can I create new double[][] before passing it to simpleRegression

Yes. For example

            double[][] data = new data[1][2];

            for(int m=0; m < segmentI; m++)
            {
                    data[0][0] = xList.get(m);
                    data[0][1] = yList.get(m);
                    simpleRegression.addData(data);
            }

You know there's also a method that you can call without an array?

simpleRegression.addData(xList.get(m), yList.get(m));

This worked with below changes:
double[][] pqr={ArrayUtils.toPrimitive(yList.toArray(new Double[0])),ArrayUtils.toPrimitive(xList.toArray(new Double[0]))};
simpleRegression.addData(pqr);