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## Random Variables

Random variables generated to conform to a specific probability distribution are fundamental to the monte-carlo process of algorithm testing and calibration. Tina provides a set of routines to support this approach. These are :

```int rand_bit()
```
Returns a random bit (i.e. 0 or 1 with probabilities 0.5).

```int rand_int(int a, int b)
```
Returns a uniformly distributed random integer x with a 5#5= x 5#5 b, (i.e. x never takes the value b).

```double rand_1()
```
Returns a uniformly distributed random double between 0.0 and 1.0.

```double rand_unif(double x, double y)
```
Returns a uniformly distributed random double between x and y.

```double rand_normal(double mu, double sigma)
```

Returns a normally distributed random double with mean mu and standard deviation sigma.

```double chisq(double x, int n)
```
Returns the confidence that a chi squared variable with n degrees of freedom is less than or equal to x.

Next: 2D and 3D vector Up: Util: Maths Utilities Previous: Complex Variables   Contents
root 2019-02-23