Continuous Stochastic Processes examples












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I am trying to understand various types of stochastic processes. In order for that to happen, I needed some simple examples to be built so that I can build an intuition about them.



According to the book of Hwei Hsu (Chapter-5, Page-161, "Description of a Random Process"), I can design the following simple and intuitive examples myself using only a standard die:



2. Continuous parameter (or Continuous-time) process



???



4. Continuous-state process



Suppose, we roll a die either a finite ($n$) number of times or an infinite number of times and plot $frac{e^{X(t)}}{1000}$ as a graph like the following:



enter image description here





My first question is: are my examples correct? If not, kindly help me to make the necessary corrections.



Secondly, what would be the example of (2)?










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  • $begingroup$
    This is not an example of what is asked for. Your parameter is discrete. What you need is something like temperature as a function of time.
    $endgroup$
    – herb steinberg
    Jan 10 at 22:09










  • $begingroup$
    @herbsteinberg how can a time be continuous if I sample it after a regular interval?
    $endgroup$
    – user366312
    Jan 11 at 14:15












  • $begingroup$
    It's continuous as long as it is a function of time. You can sample at regular or random intervals,whenever the underlying process is continuous.
    $endgroup$
    – herb steinberg
    Jan 11 at 18:04
















0












$begingroup$


I am trying to understand various types of stochastic processes. In order for that to happen, I needed some simple examples to be built so that I can build an intuition about them.



According to the book of Hwei Hsu (Chapter-5, Page-161, "Description of a Random Process"), I can design the following simple and intuitive examples myself using only a standard die:



2. Continuous parameter (or Continuous-time) process



???



4. Continuous-state process



Suppose, we roll a die either a finite ($n$) number of times or an infinite number of times and plot $frac{e^{X(t)}}{1000}$ as a graph like the following:



enter image description here





My first question is: are my examples correct? If not, kindly help me to make the necessary corrections.



Secondly, what would be the example of (2)?










share|cite|improve this question









$endgroup$












  • $begingroup$
    This is not an example of what is asked for. Your parameter is discrete. What you need is something like temperature as a function of time.
    $endgroup$
    – herb steinberg
    Jan 10 at 22:09










  • $begingroup$
    @herbsteinberg how can a time be continuous if I sample it after a regular interval?
    $endgroup$
    – user366312
    Jan 11 at 14:15












  • $begingroup$
    It's continuous as long as it is a function of time. You can sample at regular or random intervals,whenever the underlying process is continuous.
    $endgroup$
    – herb steinberg
    Jan 11 at 18:04














0












0








0





$begingroup$


I am trying to understand various types of stochastic processes. In order for that to happen, I needed some simple examples to be built so that I can build an intuition about them.



According to the book of Hwei Hsu (Chapter-5, Page-161, "Description of a Random Process"), I can design the following simple and intuitive examples myself using only a standard die:



2. Continuous parameter (or Continuous-time) process



???



4. Continuous-state process



Suppose, we roll a die either a finite ($n$) number of times or an infinite number of times and plot $frac{e^{X(t)}}{1000}$ as a graph like the following:



enter image description here





My first question is: are my examples correct? If not, kindly help me to make the necessary corrections.



Secondly, what would be the example of (2)?










share|cite|improve this question









$endgroup$




I am trying to understand various types of stochastic processes. In order for that to happen, I needed some simple examples to be built so that I can build an intuition about them.



According to the book of Hwei Hsu (Chapter-5, Page-161, "Description of a Random Process"), I can design the following simple and intuitive examples myself using only a standard die:



2. Continuous parameter (or Continuous-time) process



???



4. Continuous-state process



Suppose, we roll a die either a finite ($n$) number of times or an infinite number of times and plot $frac{e^{X(t)}}{1000}$ as a graph like the following:



enter image description here





My first question is: are my examples correct? If not, kindly help me to make the necessary corrections.



Secondly, what would be the example of (2)?







probability stochastic-processes random-variables






share|cite|improve this question













share|cite|improve this question











share|cite|improve this question




share|cite|improve this question










asked Jan 10 at 20:43









user366312user366312

593317




593317












  • $begingroup$
    This is not an example of what is asked for. Your parameter is discrete. What you need is something like temperature as a function of time.
    $endgroup$
    – herb steinberg
    Jan 10 at 22:09










  • $begingroup$
    @herbsteinberg how can a time be continuous if I sample it after a regular interval?
    $endgroup$
    – user366312
    Jan 11 at 14:15












  • $begingroup$
    It's continuous as long as it is a function of time. You can sample at regular or random intervals,whenever the underlying process is continuous.
    $endgroup$
    – herb steinberg
    Jan 11 at 18:04


















  • $begingroup$
    This is not an example of what is asked for. Your parameter is discrete. What you need is something like temperature as a function of time.
    $endgroup$
    – herb steinberg
    Jan 10 at 22:09










  • $begingroup$
    @herbsteinberg how can a time be continuous if I sample it after a regular interval?
    $endgroup$
    – user366312
    Jan 11 at 14:15












  • $begingroup$
    It's continuous as long as it is a function of time. You can sample at regular or random intervals,whenever the underlying process is continuous.
    $endgroup$
    – herb steinberg
    Jan 11 at 18:04
















$begingroup$
This is not an example of what is asked for. Your parameter is discrete. What you need is something like temperature as a function of time.
$endgroup$
– herb steinberg
Jan 10 at 22:09




$begingroup$
This is not an example of what is asked for. Your parameter is discrete. What you need is something like temperature as a function of time.
$endgroup$
– herb steinberg
Jan 10 at 22:09












$begingroup$
@herbsteinberg how can a time be continuous if I sample it after a regular interval?
$endgroup$
– user366312
Jan 11 at 14:15






$begingroup$
@herbsteinberg how can a time be continuous if I sample it after a regular interval?
$endgroup$
– user366312
Jan 11 at 14:15














$begingroup$
It's continuous as long as it is a function of time. You can sample at regular or random intervals,whenever the underlying process is continuous.
$endgroup$
– herb steinberg
Jan 11 at 18:04




$begingroup$
It's continuous as long as it is a function of time. You can sample at regular or random intervals,whenever the underlying process is continuous.
$endgroup$
– herb steinberg
Jan 11 at 18:04










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