# Difference between revisions of "Càdlàg"

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* All continuous functions are càdlàg functions. | * All continuous functions are càdlàg functions. | ||

* As a consequence of their definition, all [[cumulative distribution function]]s are càdlàg functions. | * As a consequence of their definition, all [[cumulative distribution function]]s are càdlàg functions. For instance the cumulative at point <math>r</math> correspond to the probability of being lower or equal than <math>r</math>, namely <math>\mathbb{P}[x\leq r]</math>. In other words, the semi-open [[interval (mathematics) | interval]] of concern for a two-tailed distribution <math>(-\infty, r]</math> is right-closed. | ||

* The right derivative ''f<sub>+</sub>''' of any [[convex function]] '' f'' defined on an open interval, is an increasing cadlag function. | * The right derivative ''f<sub>+</sub>''' of any [[convex function]] '' f'' defined on an open interval, is an increasing cadlag function. | ||

==Skorokhod space== | ==Skorokhod space== | ||

The set of all càdlàg functions from ''E'' to ''M'' is often denoted by {{nowrap|''D''(''E''; ''M'')}} (or simply ''D'') and is called '''Skorokhod space''' after the [[ | The set of all càdlàg functions from ''E'' to ''M'' is often denoted by {{nowrap|''D''(''E''; ''M'')}} (or simply ''D'') and is called '''Skorokhod space''' after the [[Soviet]] [[mathematician]] [[Anatoliy Skorokhod]]. Skorokhod space can be assigned a [[topology]] that, intuitively allows us to "wiggle space and time a bit" (whereas the traditional topology of [[uniform convergence]] only allows us to "wiggle space a bit"). For simplicity, take {{nowrap|''E'' {{=}} [0, ''T'']}} and {{nowrap|''M'' {{=}} '''R'''<sup>''n''</sup>}} — see Billingsley for a more general construction. | ||

We must first define an analogue of the [[modulus of continuity]], {{nowrap|''ϖ′<sub>ƒ</sub>''(''δ'')}}. For any {{nowrap|''F'' ⊆ ''E''}}, set | We must first define an analogue of the [[modulus of continuity]], {{nowrap|''ϖ′<sub>ƒ</sub>''(''δ'')}}. For any {{nowrap|''F'' ⊆ ''E''}}, set | ||

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\sigma (f, g) := \inf_{\lambda \in \Lambda} \max \{ \| \lambda - I \|, \| f - g \circ \lambda \| \}, | \sigma (f, g) := \inf_{\lambda \in \Lambda} \max \{ \| \lambda - I \|, \| f - g \circ \lambda \| \}, | ||

</math> | </math> | ||

where {{nowrap|''I'': ''E'' → ''E''}} is the identity function. In terms of the"wiggle" intuition, {{nowrap|{{!!}}''λ − I''{{!!}}}} measures the size of the"wiggle in time", and {{nowrap|{{!!}}''ƒ − g○λ''{{!!}}}} measures the size of the"wiggle in space". | where {{nowrap|''I'': ''E'' → ''E''}} is the identity function. In terms of the "wiggle" intuition, {{nowrap|{{!!}}''λ − I''{{!!}}}} measures the size of the "wiggle in time", and {{nowrap|{{!!}}''ƒ − g○λ''{{!!}}}} measures the size of the "wiggle in space". | ||

It can be shown that the Skorokhod [[Metric (mathematics)|metric]] is | It can be shown that the Skorokhod [[Metric (mathematics)|metric]] is indeed a metric. The topology Σ generated by ''σ'' is called the '''Skorokhod topology''' on ''D''. | ||

==Properties of Skorokhod space== | ==Properties of Skorokhod space== | ||

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Under the Skorokhod topology and pointwise addition of functions, ''D'' is not a topological group, as can be seen by the following example: | Under the Skorokhod topology and pointwise addition of functions, ''D'' is not a topological group, as can be seen by the following example: | ||

Let <math> E=[0,2) </math> be the unit interval and take <math>f_n = \chi_{[1/n,2)} \in D</math> to be a sequence of characteristic functions. | Let <math> E=[0,2) </math> be the unit interval and take <math>f_n = \chi_{[1-1/n,2)} \in D</math> to be a sequence of characteristic functions. | ||

Despite the fact that <math> f_n \rightarrow \chi_{[1,2)} </math> in the Skorokhod topology, the sequence <math> f_n - \chi_{[1,2)} </math> does not converge to 0. | Despite the fact that <math> f_n \rightarrow \chi_{[1,2)} </math> in the Skorokhod topology, the sequence <math> f_n - \chi_{[1,2)} </math> does not converge to 0. | ||

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{{DEFAULTSORT:Cadlag}} | {{DEFAULTSORT:Cadlag}} | ||

## Latest revision as of 13:36, 25 May 2014

In mathematics, a **càdlàg** (French "continue à droite, limite à gauche"), **RCLL** (“right continuous with left limits”), or **corlol** (“continuous on (the) right, limit on (the) left”) function is a function defined on the real numbers (or a subset of them) that is everywhere right-continuous and has left limits everywhere. Càdlàg functions are important in the study of stochastic processes that admit (or even require) jumps, unlike Brownian motion, which has continuous sample paths. The collection of càdlàg functions on a given domain is known as **Skorokhod space**.

Two related terms are **càglàd**, standing for "continue à gauche, limite à droite", the left-right reversal of càdlàg, and **càllàl** for"continue à l'un, limite à l’autre" (continuous on one side, limit on the other side), for a function which is interchangeably either càdlàg or càglàd at each point of the domain.

## Definition

Let (*M*, *d*) be a metric space, and let *E* ⊆ **R**. A function *ƒ*: *E* → *M* is called a **càdlàg function** if, for every *t* ∈ *E*,

- the left limit
*ƒ*(*t−*) := lim_{s↑t}*ƒ*(*s*) exists; and - the right limit
*ƒ*(*t+*) := lim_{s↓t}*ƒ*(*s*) exists and equals*ƒ*(*t*).

That is, *ƒ* is right-continuous with left limits.

## Examples

- All continuous functions are càdlàg functions.
- As a consequence of their definition, all cumulative distribution functions are càdlàg functions. For instance the cumulative at point correspond to the probability of being lower or equal than , namely . In other words, the semi-open interval of concern for a two-tailed distribution is right-closed.
- The right derivative
*f*of any convex function_{+}'*f*defined on an open interval, is an increasing cadlag function.

## Skorokhod space

The set of all càdlàg functions from *E* to *M* is often denoted by *D*(*E*; *M*) (or simply *D*) and is called **Skorokhod space** after the Soviet mathematician Anatoliy Skorokhod. Skorokhod space can be assigned a topology that, intuitively allows us to "wiggle space and time a bit" (whereas the traditional topology of uniform convergence only allows us to "wiggle space a bit"). For simplicity, take *E* = [0, *T*] and *M* = **R**^{n} — see Billingsley for a more general construction.

We must first define an analogue of the modulus of continuity, *ϖ′ _{ƒ}*(

*δ*). For any

*F*⊆

*E*, set

and, for *δ* > 0, define the **càdlàg modulus** to be

where the infimum runs over all partitions Π = {0 = *t*_{0} < *t*_{1} < … < *t _{k} = T*},

*k*∈

**N**, with min

_{i}(

*t*

_{i}− t_{i−1}) >

*δ*. This definition makes sense for non-càdlàg

*ƒ*(just as the usual modulus of continuity makes sense for discontinuous functions) and it can be shown that

*ƒ*is càdlàg if and only if

*ϖ′*(

_{ƒ}*δ*) → 0 as

*δ*→ 0.

Now let Λ denote the set of all strictly increasing, continuous bijections from *E* to itself (these are "wiggles in time"). Let

denote the uniform norm on functions on *E*. Define the **Skorokhod metric** *σ* on *D* by

where *I*: *E* → *E* is the identity function. In terms of the "wiggle" intuition, Template:!!*λ − I*Template:!! measures the size of the "wiggle in time", and Template:!!*ƒ − g○λ*Template:!! measures the size of the "wiggle in space".

It can be shown that the Skorokhod metric is indeed a metric. The topology Σ generated by *σ* is called the **Skorokhod topology** on *D*.

## Properties of Skorokhod space

### Generalization of the uniform topology

The space *C* of continuous functions on *E* is a subspace of *D*. The Skorokhod topology relativized to *C* coincides with the uniform topology there.

### Completeness

It can be shown (Convergence of probability measures - Billingsley 1999) that, although *D* is not a complete space with respect to the Skorokhod metric *σ*, there is a topologically equivalent metric *σ*_{0} with respect to which *D* is complete.

### Separability

With respect to either *σ* or *σ*_{0}, *D* is a separable space. Thus, Skorokhod space is a Polish space.

### Tightness in Skorokhod space

By an application of the Arzelà–Ascoli theorem, one can show that a sequence (*μ _{n}*)

_{n=1,2,…}of probability measures on Skorokhod space

*D*is tight if and only if both the following conditions are met:

and

### Algebraic and topological structure

Under the Skorokhod topology and pointwise addition of functions, *D* is not a topological group, as can be seen by the following example:

Let be the unit interval and take to be a sequence of characteristic functions. Despite the fact that in the Skorokhod topology, the sequence does not converge to 0.

## References

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