DiscreteMaxLimit
DiscreteMaxLimit[f,k∞]
gives the max limit k∞f(k) of the sequence f as k tends to ∞ over the integers.
DiscreteMaxLimit[f,{k1,…,kn}]
gives the nested max limit ⋯ f(k1,…,kn) over the integers.
DiscreteMaxLimit[f,{k1,…,kn}{,…,}]
gives the multivariate max limit f(k1,…,kn) over the integers.
Details and Options
- DiscreteMaxLimit is also known as limit superior, supremum limit, limsup, upper limit and outer limit.
- DiscreteMaxLimit computes the smallest upper bound for the limit and is always defined for real-valued sequences. It is often used to give conditions of convergence and other asymptotic properties that do not rely on an actual limit to exist.
- DiscreteMaxLimit[f,k∞] can be entered as f. A template can be entered as dMlim, and moves the cursor from the underscript to the body.
- DiscreteMaxLimit[f,{k1,…,kn}{,…,}] can be entered as …f.
- The possible limit points are ±∞.
- The max limit is defined as a limit of the max envelope sequence max[ω]:
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DiscreteMaxLimit[f,k∞] DiscreteLimit[max[ω],ω∞] DiscreteMaxLimit[f,{k1,…,kn}{∞,…,∞}] DiscreteLimit[max[ω],ω∞] - DiscreteMaxLimit[f[k],k-∞] is equivalent to DiscreteMaxLimit[f[-l],l∞] etc.
- The definition uses the max envelope max[ω]MaxValue[{f[k],k≥ω∧k∈},k] for univariate f[k] and max[ω]MaxValue[{f[k1,…,kn],k1≥ω∧⋯∧kn≥ω∧ki∈},{k1,…,kn}] for multivariate f[k1,…,kn]. The sequence max[ω] is monotone decreasing as ω∞, so it always has a limit, which may be ±∞.
- The illustration shows max[k] and max[Min[k1,k2]] in blue.
- DiscreteMaxLimit returns unevaluated when the max limit cannot be found.
- The following options can be given:
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Assumptions $Assumptions assumptions on parameters GenerateConditions Automatic whether to generate conditions on parameters Method Automatic method to use PerformanceGoal "Quality" aspects of performance to optimize - Possible settings for GenerateConditions include:
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Automatic non-generic conditions only True all conditions False no conditions None return unevaluated if conditions are needed - Possible settings for PerformanceGoal include $PerformanceGoal, "Quality" and "Speed". With the "Quality" setting, DiscreteMaxLimit typically solves more problems or produces simpler results, but it potentially uses more time and memory.
Examples
open allclose allBasic Examples (4)
Use dMlim to enter the template and to move from the underscript to the body:
TraditionalForm typesetting:
Scope (21)
Basic Uses (4)
Elementary Sequences (6)
Periodic Sequences (3)
Piecewise Sequences (2)
Special Function Sequences (2)
Options (6)
Assumptions (1)
GenerateConditions (3)
Return a result without stating conditions:
This result is only valid if x>1:
Return unevaluated if the results depend on the value of parameters:
By default, conditions are generated that return a unique result:
By default, conditions are not generated if only special values invalidate the result:
With GenerateConditions->True, even these non-generic conditions are reported:
Method (1)
PerformanceGoal (1)
DiscreteMaxLimit computes limits involving sequences of arbitrarily large periods:
Use PerformanceGoal to avoid potentially expensive computations in such cases:
The Method option overrides PerformanceGoal:
Applications (7)
Basic Applications (2)
Compute the asymptotic supremum of a sequence:
Plot the sequence and the asymptotic supremum:
Verify that the following sequence does not have a limit:
Show that DiscreteMaxLimit and DiscreteMinLimit are not equal:
Confirm that the limit does not exist by using DiscreteLimit:
Series Convergence (4)
Show that the infinite series whose general term is defined here is convergent, by using the ratio test:
Plot the partial sums of the series:
Compute the ratio of the adjacent terms using DiscreteRatio:
The sequence of ratios does not converge:
However, the ratio test can still be used because the upper limit of the ratios is less than 1:
Confirm that the series converges using SumConvergence:
Show that the infinite series whose general term is defined here is convergent, by using the root test:
Plot the partial sums of the series:
Compute the n root of the general term:
The limit of the sequence of roots does not exist:
However, the root test still indicates convergence because the max limit is less than 1:
Confirm that the series converges using SumConvergence:
The inverse radius of the associated power series is given by:
This means the radius of convergence is infinite and converges for all , in particular to :
Compute the Taylor series at zero and its radius of convergence for the following function:
Formally, the Taylor series does sum to the original function:
The radius of convergence of the Taylor series is given by:
This means the Taylor series will converge for values of within of the origin. For example, at :
At values of further away, the sum will not converge; for example, at :
At the points , the terms of the Taylor series alternate between and :
Hence the partial sums go between and :
Visualize and the partial sums of its Taylor series on the interval ; in the interior of the interval, convergence is rapid, but the Taylor polynomials always go to either or at the endpoints:
Computational Complexity (1)
An algorithm runtime function is said to be "big-o of ", written , if :
Similarly, is said to be "big-theta of ", written if and :
It is possible for two functions to share neither relationship:
Hence, defines a reflexive partial order on the space of algorithm runtimes similar to :
If and , then , which implies that is an equivalence relation:
Properties & Relations (11)
A real-valued sequence always has a (possibly infinite) max limit:
The corresponding limit may not exist:
If and have finite max limits, then :
In this case, there is strict inequality:
Positive multiplicative constants can be moved outside a limit:
For a real-valued sequence, if DiscreteLimit exists, DiscreteMaxLimit has the same value:
DiscreteMaxLimit is always greater than or equal to DiscreteMinLimit:
If DiscreteMaxLimit equals DiscreteMinLimit, the limit exists and equals their common value:
If the max limit is , then the min limit and thus the limit are also :
DiscreteMaxLimit can be computed as -DiscreteMinLimit[-f,…]:
If the two max limits are equal—as in this example—then has a limit:
This is a generalization of the "squeezing" or "sandwich" theorem:
MaxLimit is always greater than or equal to DiscreteMaxLimit:
Possible Issues (1)
DiscreteMaxLimit is only defined for real-valued sequences:
Text
Wolfram Research (2017), DiscreteMaxLimit, Wolfram Language function, https://reference.wolfram.com/language/ref/DiscreteMaxLimit.html.
CMS
Wolfram Language. 2017. "DiscreteMaxLimit." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/DiscreteMaxLimit.html.
APA
Wolfram Language. (2017). DiscreteMaxLimit. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/DiscreteMaxLimit.html