0
$\begingroup$

The intensity function is defined as

$$\lambda^*(t)=\frac{f(t|H_{t_n})}{1-F(t|H_{t_n})}$$ where $f$ is the density function and $F$ is the distribution function, and $H_{t_n}$ is the history of all the previous points of $t$ up to $t_n$. Moreover, there is proven that $F(t|H_{t_n})$ is also given as:

$$F(t|H_{t_n})=1-e^{-\int_{t_n}^t\lambda^*(s)ds}$$.

An assumption is then made, saying that

  1. $\lambda^*(t)$ is non-negative and is integrable on every interval after $t_n$.

  2. $\int_{t_n}^t\lambda^*(s)ds \to 1$ for $t \to \infty$.

It is then said that hence the three points follows:

  1. $0 \leq F(t|H_{t_n}) \leq 1$
  2. $F(t|H_{t_n})$ is a non-decreasing function of $t$.
  3. $F(t|H_{t_n}) \to 1$ for $t \to \infty$

Can someone explain to me how these three points follow given the two assumptions above? Thank you.

$\endgroup$
12
  • 2
    $\begingroup$ Without knowing the paper you start with who shall answer your question? Is there a underlying stochastic process? What? $\endgroup$ Commented Jan 19, 2021 at 21:49
  • 1
    $\begingroup$ Yasmin: in its current form, the question might be more suitable for stats.stackexchange.com just because it is using terminology/definitions/conventions that are tacitly understood in that setting. $\endgroup$
    – Yemon Choi
    Commented Jan 19, 2021 at 22:15
  • 1
    $\begingroup$ For a start, if you have tried to derive point 1 from the given information, at which point did you get stuck? $\endgroup$
    – Yemon Choi
    Commented Jan 19, 2021 at 22:15
  • 2
    $\begingroup$ Rather than just answering what the paper's about, why not also mention the specific paper? $\endgroup$
    – LSpice
    Commented Jan 20, 2021 at 0:26
  • 2
    $\begingroup$ @LSpice: Sure, the paper I'm reading is in this link arxiv.org/pdf/1806.00221.pdf, and the proof, or the proposition, is in page 9. $\endgroup$
    – Yasmin
    Commented Jan 20, 2021 at 10:55

0

You must log in to answer this question.

Browse other questions tagged .