Java uses Colt for probability distribution analysis and statistical data analysis
Colt is a Java library used for probability distribution analysis and statistical data analysis. It provides a set of high-performance mathematical functions and algorithms that can be used to generate random numbers, calculate statistical indicators, fit probability distributions, perform matrix operations, and more.
Maven coordinates:
<dependencies>
<dependency>
<groupId>cern.colt</groupId>
<artifactId>colt</artifactId>
<version>1.2.0</version>
</dependency>
</dependencies>
Colt mainly includes the following modules:
1. Colt Core: Provides basic matrix operations, including matrix creation, operation, and transpose.
2. Colt Random: used to generate random numbers, including uniform distribution, Normal distribution and Poisson distribution. It has high performance and repeatability.
3. Colt Stat: Provides calculations for various statistical functions and indicators, such as mean, variance, covariance, etc.
4. Colt Fit: used to fit the probability distribution to the observed data, including Normal distribution, Exponential distribution, Log-normal distribution, etc.
The following is an example code for using Colt for probability distribution analysis and statistical data analysis:
import cern.colt.list.DoubleArrayList;
import cern.jet.random.Normal;
import cern.jet.random.engine.MersenneTwister;
import cern.jet.stat.Descriptive;
import cern.jet.stat.Probability;
public class ColtExample {
public static void main(String[] args) {
//Generate 1000 random numbers subject to Normal distribution
MersenneTwister randomGenerator = new MersenneTwister();
Normal normalDistribution = new Normal(0, 1, randomGenerator);
DoubleArrayList data = new DoubleArrayList();
for (int i = 0; i < 1000; i++) {
data.add(normalDistribution.nextDouble());
}
//Calculate mean and standard deviation
double mean = Descriptive.mean(data);
double stddev = Descriptive.standardDeviation(data, mean);
//Judge whether to obey Normal distribution
boolean isNormal = Probability.normalInverse(mean, stddev, 0.95) < 1.96;
System.out.println("Mean: " + mean);
System.out.println("Standard Deviation: " + stddev);
System.out.println("Is Normal: " + isNormal);
}
}
In the above code, first use Colt's random number generator to generate 1000 random numbers that obey the standard Normal distribution, and then use Colt's statistical function to calculate the mean and standard deviation of these data. Finally, judge whether the data obey the Normal distribution by judging whether the 95% confidence interval contains 1.96.
Summary:
Colt is a powerful Java library suitable for probability distribution analysis and statistical data analysis. It provides many high-performance mathematical functions and algorithms that can be used to generate random numbers, calculate statistical indicators, fit probability distributions, and more. Using Colt can facilitate statistical analysis and has high performance and accuracy.
