covariance

I have some problems with the transformation of a matrix and the names of the rows and columns. My problem is as follows: As input-matrix I have a (symmetric) correlation matrix like this one: The correlation-vector is given by the values of the lower triangular matrix: Now, I want to compute the variance-covariance-matrix of the these correlations, which are approximately normally distributed with the variance-covariance-matrix : The variances can be approximated by -> N is the sample size (in this example N = 66) The covariances can be approximated by For example the covariance between r_02

I'm having a struggle understanding these two concepts. But I think after many videos and SO QA's, I have it distilled down to its simplest form: Covariant - Assumes a sub-type can do what its base-type does. Contravariant - Assumes you can treat a sub-type the same way you would treat its base-type. Supposing these three classes: class Animal { void Live(Animal animal) { //born! } void Die(Animal animal) { //dead! } } class Cat : Animal { } class Dog : Animal { } Covariant Any animal can do what animals do. Assumes a sub-type can do what its base-type does. Animal anAnimal = new Cat();

I'm trying to overrun quite big (for me) problem that I came across while writing my application. Look at this, please (I will try to shorten the code for simplicity): I have root interface called IRepository<T> . Next, IBookRepository : IRepository<Book> Next, concrete class that implements it: BookRepository : IBookRepository In the RepositoryManager class I declared private IRepository<IRepoItem> currentRepo; IRepoItem is an interface that is implemented by Book class. Now, when I try to do something like this: currentRepo = new BookRepository(); VisualStudio gives error message: Cannot

Inspired by Real-world examples of co- and contravariance in Scala I thought a better question would be: When designing a library, are there a specific set of questions you should ask yourself when determining whether a type parameter should be covariant or contravariant? Or should you make everything invariant and then change as needed? Well, simple, does it make sense? Think of Liskov substitution. Co-variance If A <: B , does it make sense to pass a C[A] where a C[B] is expected? If so, make it C[+T] . The classic example is the immutable List , where a List[A] can be passed to anything

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 由 翻译 强力驱动 问题: I know this question has already been asked a couple of times, but I couldn't find a solution to my problem. I don't have more variables than observations and I don't have NAN values in my matrix. Here's my function: function [ ind , idx_ran ] = fselect ( features_f , class_f , dir ) idx = linspace ( 1 , size ( features_f , 2 ), size ( features_f , 2 )); idx_ran = idx (:, randperm ( size ( features_f , 2 ))); features_t_ran = features_f (:, idx_ran ); % randomize colums len = length ( class_f ); r = randi ( len , [ 1 , round ( len

The definition System.Linq.ILookUp reads interface ILookup<TKey, TElement> : IEnumerable<IGrouping<TKey, TElement>>, IEnumerable { int Count { get; } IEnumerable<TElement> this[TKey key] { get; } bool Contains(TKey key); } Since IEnumerable is covariant in IGrouping<TKey, TElement>, IGrouping<TKey, TElement> is covariant in TElement and the interface only exposes TElement as a return type, I would assume that ILookup is also covariant in TElement. Indeed, the definition interface IMyLookup<TKey, out TElement> : IEnumerable<IGrouping<TKey, TElement>>, IEnumerable { int Count { get; }

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 由 翻译 强力驱动 问题: I'm trying to calculate the mahalanobis distance with c#. I can't find any real good examples online and I'm new to C#. I am especially having trouble getting the covariance matrix to run right. Any help would be appreciated. Thanks! using System ; using System . Collections . Generic ; using System . Linq ; using System . Text ; using System . Threading . Tasks ; using MathNet . Numerics . LinearAlgebra . Double ; namespace MahalanobisDistance { class Program { static void Main ( string [] args ) { Program p = new Program ();

What is the meaning of the concepts 'covariance' and 'contravariance'? Given 2 classes, Animal and Elephant (which inherits from Animal ), my understanding is that you would get a run-time errors if you try and put an Elephant into an array of Animals, and this happens because Elephant is "bigger" (more specific) than Animal. But could you place an Animal into an array of Elephant, seeing how Elephant is guaranteed to contain the Animal properties? You have it backwards. You can add an Elephant to an Animal array because it is an Animal, and it's guaranteed to have all of the methods an Animal

I'm stuck trying to translate some Java code that uses (bounded) wildcard generics to C#. My problem is, Java seems to allow a generic type to be both covariant and contravariant when used with a wildcard. [This is a spin-off from a previous question dealing with a simpler case of bounded-wildcards] Java - works: class Impl { } interface IGeneric1<T extends Impl> { void method1(IGeneric2<?> val); T method1WithParam(T val); } interface IGeneric2<T extends Impl> { void method2(IGeneric1<?> val); } abstract class Generic2<T extends Impl> implements IGeneric2<T> { // !! field using wildcard