Out Of Sample Error Definition
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here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings out of sample definition and policies of this site About Us Learn more about Stack Overflow in sample and out of sample forecasting the company Business Learn more about hiring developers or posting ads with us Stack Overflow Questions Jobs Documentation Tags in sample vs out of sample error Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 6.2 million programmers, just like you, helping each other. Join them; it only out of sample forecast definition takes a minute: Sign up out of sample definition [closed] up vote 3 down vote favorite can any one explain me about the out of sampling and in sampling. statistics computational-finance share|improve this question asked Feb 23 '11 at 6:16 Amber 47129 closed as not a real question by joran, Tchoupi, Troy Alford, joce, DarkAjax Mar 20 '13 at 22:02
In Sample Meaning
It's difficult to tell what is being asked here. This question is ambiguous, vague, incomplete, overly broad, or rhetorical and cannot be reasonably answered in its current form. For help clarifying this question so that it can be reopened, visit the help center.If this question can be reworded to fit the rules in the help center, please edit the question. What, specifically, are you talking about? Are you talking about data points that lie outside of the sampling distribution mean? –Cody Gray Feb 23 '11 at 6:29 add a comment| 2 Answers 2 active oldest votes up vote 4 down vote It is statistics speak which in most cases means "using past data to make forecasts of the future". "In sample" refers to the data that you have, and "out of sample" to the data you don't have but want to forecast or estimate. share|improve this answer answered Mar 30 '11 at 18:18 Brian 412 add a comment| Did you find this question interesting? Try our newsletter Sign up for our newsletter and get our top new quest
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Out Of Sample Analysis
company Business Learn more about hiring developers or posting ads with us Cross Validated out of sample performance Questions Tags Users Badges Unanswered Ask Question _ Cross Validated is a question and answer site for people interested in statistics, machine out of sample validation learning, data analysis, data mining, and data visualization. Join them; it only takes a minute: Sign up Here's how it works: Anybody can ask a question Anybody can answer The best answers are voted up and rise http://stackoverflow.com/questions/5087635/out-of-sample-definition to the top Difference between “in-sample” and “pseudo out-of-sample” forecasts up vote 2 down vote favorite 1 Probably a very basic question to the forecasters around here, but I was wondering whether there is an explicit difference between in-sample forecasts and pseudo out-of-sample forecasts. Both is meant in the context of evaluating and comparing forecasting models. forecasting share|improve this question asked Nov 7 '13 at 13:11 altabq 3011413 add a comment| 1 Answer 1 http://stats.stackexchange.com/questions/74865/difference-between-in-sample-and-pseudo-out-of-sample-forecasts active oldest votes up vote 7 down vote accepted Suppose you have data $\{Y_t,X_{t-h}\}_{t=h+1}^T$, where $h \in \{1,2,\ldots\},$ and your goal is to build a model (say, $\hat f(X_{t-h})$) to predict $Y_t$ given $X_{t-h}$. For concreteness, suppose the data is daily and $T$ corresponds to today. In-sample analysis means to estimate the model using all available data up to and including $T$, and then compare the model's fitted values to the actual realizations. However, this procedure is known to draw an overly optimistic picture of the model's forecasting ability, since common fitting algorithms (e.g. using squared error or likelihood criteria) tend to take pains to avoid large prediction errors, and are thus susceptible to overfitting - mistaking noise for signal in the data. A true out-of-sample analysis would be to estimate the model based on data up to and including today, construct a forecast of tomorrow's value $Y_{T+1}$, wait until tomorrow, record the forecast error $e_{T+1} \equiv Y_{T+1} - \hat f(X_{T+1-h}),$ re-estimate the model, make a new forecast of $Y_{T+2}$, and so forth. At the end of this exercise, one would have a sample of forecast errors $\{e_{T+l}\}_{l=1}^L$ which would be truly out-of-sample and would give a very realistic picture of the model's performance. Since this procedure is very time-consuming, people often resort to "pseudo", or "simulated", out-of-sample analy
"out-of-sample" Discussion in 'P1.T2. Quantitative Methods (20%)' started by dennis_cmpe, Nov 5, 2008. dennis_cmpe New Member What is meant by "in sample" and "out of sample" in the answer below? Question: What are http://www.bionicturtle.com/forum/threads/meaning-of-in-sample-and-out-of-sample.784/ the problems in applying GARCH(1,1)? Answer: GARCH(1,1) is less restrictive than RiskMetrics, but that is theoretically good (more flexible model with more parameters). It's key problem is that is excels in sample but forecasting, by defintion, is about making "out of sample" estimates. dennis_cmpe, Nov 5, 2008 #1 David Harper CFA FRM David Harper CFA FRM (test) This is from the Linda Allen chapter. If you collect, say, three years of return out of data to calculate the volatility, the GARCH(1,1) model for volatility within that period is "in sample." But when you use the historical data to forecast forward, you are estimating into time period without data (out of sample). So usually "out of sample" is code for "forecasting into where we don't have data" which, in practical terms, is typically what we are doing. Technically, even using the GARCH(1,1) to estimate today's volatility based out of sample on the historical sample is an "out of sample" forecast because we don't have the instantaneous volatility. David David Harper CFA FRM, Nov 6, 2008 #2 (You must log in or sign up to reply here.) Show Ignored Content Share This Page Tweet Log in with Facebook Your name or email address: Password: Forgot your password? Stay logged in Bionic Turtle Home Forums > Financial Risk Manager (FRM). Free resource > P1.T2. Quantitative Methods (20%) > Home Forums Forums Quick Links Search Forums Recent Posts Resources Resources Quick Links Search Resources Most Active Authors Latest Reviews Menu Search Search titles only Posted by Member: Separate names with a comma. Newer Than: Search this thread only Search this forum only Display results as threads Useful Searches Recent Posts More... Style Bionic Turtle 2015 Contact Us Help Home Top RSS About Us Your Bionic Turtle Team Testimonials Blog FAQs Contact Why Take the Exam? FRM Exam Overview and Registration Guide Why is FRM Certification Important? FRM Syllabus Comparison of the FRM vs CFA Designations The Vast Selection of FRM Jobs Exam Preparation Using an FRM Course FRM Study Planner Features & Pricing Partner Products Stay connected We'll keep you informed on new forum posts, relevant blog articles, and everything you'll need to prepare for your exam.YoutubeGoogle +L