In mathematics, the comparison test, sometimes called the direct comparison test to distinguish it from similar related tests (especially the limit comparison test), provides a way of deducing the convergence or divergence of an infinite series or an improper integral. In both cases, the test works by comparing the given series or integral to one whose convergence properties are known.
In calculus, the comparison test for series typically consists of a pair of statements about infinite series with non-negative (real-valued) terms:
If the infinite series converges and for all sufficiently large n (that is, for all for some fixed value N), then the infinite series also converges.
If the infinite series diverges and for all sufficiently large n, then the infinite series also diverges.
Note that the series having larger terms is sometimes said to dominate (or eventually dominate) the series with smaller terms.
Alternatively, the test may be stated in terms of absolute convergence, in which case it also applies to series with complex terms:
If the infinite series is absolutely convergent and for all sufficiently large n, then the infinite series is also absolutely convergent.
If the infinite series is not absolutely convergent and for all sufficiently large n, then the infinite series is also not absolutely convergent.
Note that in this last statement, the series could still be conditionally convergent; for real-valued series, this could happen if the an are not all nonnegative.
The second pair of statements are equivalent to the first in the case of real-valued series because converges absolutely if and only if , a series with nonnegative terms, converges.
The proofs of all the statements given above are similar. Here is a proof of the third statement.
Let and be infinite series such that converges absolutely (thus converges), and without loss of generality assume that for all positive integers n. Consider the partial sums
Since converges absolutely, for some real number T. For all n,
is a nondecreasing sequence and is nonincreasing.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
In mathematics, the root test is a criterion for the convergence (a convergence test) of an infinite series. It depends on the quantity where are the terms of the series, and states that the series converges absolutely if this quantity is less than one, but diverges if it is greater than one. It is particularly useful in connection with power series. The root test was developed first by Augustin-Louis Cauchy who published it in his textbook Cours d'analyse (1821). Thus, it is sometimes known as the Cauchy root test or Cauchy's radical test.
In mathematics, a series is the sum of the terms of an infinite sequence of numbers. More precisely, an infinite sequence defines a series S that is denoted The nth partial sum Sn is the sum of the first n terms of the sequence; that is, A series is convergent (or converges) if the sequence of its partial sums tends to a limit; that means that, when adding one after the other in the order given by the indices, one gets partial sums that become closer and closer to a given number.
In mathematics, the ratio test is a test (or "criterion") for the convergence of a series where each term is a real or complex number and an is nonzero when n is large. The test was first published by Jean le Rond d'Alembert and is sometimes known as d'Alembert's ratio test or as the Cauchy ratio test. The usual form of the test makes use of the limit The ratio test states that: if L < 1 then the series converges absolutely; if L > 1 then the series diverges; if L = 1 or the limit fails to exist, then the test is inconclusive, because there exist both convergent and divergent series that satisfy this case.
This work studies the problem of statistical inference for Fréchet means in the Wasserstein space of measures on Euclidean spaces, W2(Rd). This question arises naturally from the problem of separating amplitude and phase variation i ...
Generalized linear models, where a random vector x is observed through a noisy, possibly nonlinear, function of a linear transform z = A x, arise in a range of applications in nonlinear filtering and regression. Approximate message passing (AMP) methods, b ...
Generalized Linear Models (GLMs), where a random vector x is observed through a noisy, possibly nonlinear, function of a linear transform z = A x arise in a range of applications in nonlinear filtering and regression. Approximate Message Passing (AMP) meth ...