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  2. Limit of a sequence - Wikipedia

    en.wikipedia.org/wiki/Limit_of_a_sequence

    Here, one can see that the sequence is converging to the limit 0 as n increases. In the real numbers , a number L {\displaystyle L} is the limit of the sequence ( x n ) {\displaystyle (x_{n})} , if the numbers in the sequence become closer and closer to L {\displaystyle L} , and not to any other number.

  3. Convergence of random variables - Wikipedia

    en.wikipedia.org/wiki/Convergence_of_random...

    As an example one may consider random variables with densities f n (x) = (1 + cos(2πnx))1 (0,1). These random variables converge in distribution to a uniform U(0, 1), whereas their densities do not converge at all. [3] However, according to Scheffé’s theorem, convergence of the probability density functions implies convergence in ...

  4. Convergent series - Wikipedia

    en.wikipedia.org/wiki/Convergent_series

    If r < 1, then the series is absolutely convergent. If r > 1, then the series diverges. If r = 1, the ratio test is inconclusive, and the series may converge or diverge. Root test or nth root test. Suppose that the terms of the sequence in question are non-negative. Define r as follows:

  5. Alternating series - Wikipedia

    en.wikipedia.org/wiki/Alternating_series

    Like any series, an alternating series is a convergent series if and only if the sequence of partial sums of the series converges to a limit. The alternating series test guarantees that an alternating series is convergent if the terms a n converge to 0 monotonically , but this condition is not necessary for convergence.

  6. Sequence space - Wikipedia

    en.wikipedia.org/wiki/Sequence_space

    The spaces c 0 and ℓ p (for 1 ≤ p < ∞) have a canonical unconditional Schauder basis {e i | i = 1, 2,...}, where e i is the sequence which is zero but for a 1 in the i th entry. The space ℓ 1 has the Schur property: In ℓ 1, any sequence that is weakly convergent is also strongly convergent .

  7. Proofs of convergence of random variables - Wikipedia

    en.wikipedia.org/wiki/Proofs_of_convergence_of...

    Each of the probabilities on the right-hand side converge to zero as n → ∞ by definition of the convergence of {X n} and {Y n} in probability to X and Y respectively. Taking the limit we conclude that the left-hand side also converges to zero, and therefore the sequence {(X n, Y n)} converges in probability to {(X, Y)}.

  8. Cauchy sequence - Wikipedia

    en.wikipedia.org/wiki/Cauchy_sequence

    The utility of Cauchy sequences lies in the fact that in a complete metric space (one where all such sequences are known to converge to a limit), the criterion for convergence depends only on the terms of the sequence itself, as opposed to the definition of convergence, which uses the limit value as well as the terms.

  9. Modes of convergence - Wikipedia

    en.wikipedia.org/wiki/Modes_of_convergence

    Absolute convergence implies Cauchy convergence of the sequence of partial sums (by the triangle inequality), which in turn implies absolute convergence of some grouping (not reordering). The sequence of partial sums obtained by grouping is a subsequence of the partial sums of the original series.