Talk:2048: Curve-Fitting - Revision history

172.68.186.106 at 18:37, 9 August 2024

2024-08-09T18:37:07Z

RadiantRainwing at 16:29, 9 August 2024

2024-08-09T16:29:00Z

162.158.154.150 at 19:56, 3 April 2023

2023-04-03T19:56:15Z

172.69.62.172 at 18:28, 2 September 2019

2019-09-02T18:28:21Z

Dgbrt at 23:09, 8 November 2018

2018-11-08T23:09:09Z

108.162.246.191: Logistic curve

2018-11-08T15:31:06Z

Logistic curve

Redbelly98: Why I deleted the "+ c" term in the logarithmic and exponential functions.

2018-10-13T19:52:16Z

Why I deleted the "+ c" term in the logarithmic and exponential functions.

JohnWhoIsNotABot at 21:44, 24 September 2018

2018-09-24T21:44:04Z

172.68.34.34: Added information about Piecewise model

2018-09-21T22:05:28Z

Added information about Piecewise model

Dgbrt at 20:32, 21 September 2018

2018-09-21T20:32:28Z

← Older revision		Revision as of 18:37, 9 August 2024
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	As learnt in college, where trying to build an overlapping polynomial equation to a graph would create a working model until you move to the side and see the equation that worked until now going way off base 19:56, 3 April 2023 (UTC)D		As learnt in college, where trying to build an overlapping polynomial equation to a graph would create a working model until you move to the side and see the equation that worked until now going way off base 19:56, 3 April 2023 (UTC)D

−	Seriously? This is a big round number people, and also the name of a game that was referenced earlier in [https://xkcd.com/1350/ 1350:Lorenz]. I wish the comic acknowledged that.	+	Seriously? This is a big round number people, and also the name of a game that was referenced earlier in [https://xkcd.com/1350/ 1350:Lorenz]. I wish the comic acknowledged that. {{unsigned\|RadiantRainwing\|16:29, 9 August 2024}}

← Older revision		Revision as of 16:29, 9 August 2024
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	As learnt in college, where trying to build an overlapping polynomial equation to a graph would create a working model until you move to the side and see the equation that worked until now going way off base 19:56, 3 April 2023 (UTC)D		As learnt in college, where trying to build an overlapping polynomial equation to a graph would create a working model until you move to the side and see the equation that worked until now going way off base 19:56, 3 April 2023 (UTC)D
		+
		+	Seriously? This is a big round number people, and also the name of a game that was referenced earlier in [https://xkcd.com/1350/ 1350:Lorenz]. I wish the comic acknowledged that.

← Older revision		Revision as of 19:56, 3 April 2023
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	Personally, I think the exponential fit seems like the most reasonable interpretation of the data.		Personally, I think the exponential fit seems like the most reasonable interpretation of the data.
		+
		+	'''Is the bottom right one considered as part of the Runge Phenomenon?"
		+
		+	As learnt in college, where trying to build an overlapping polynomial equation to a graph would create a working model until you move to the side and see the equation that worked until now going way off base 19:56, 3 April 2023 (UTC)D

← Older revision		Revision as of 18:28, 2 September 2019
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	The explanation for logistic curve currently says it is used for binary values. It's actually a lot more useful than that. For example, population growth is often described as a logistic curve. It appears to be climbing exponentially initially, but then tapers off as resources can no longer support the population. [[Special:Contributions/108.162.246.191\|108.162.246.191]] 15:31, 8 November 2018 (UTC)		The explanation for logistic curve currently says it is used for binary values. It's actually a lot more useful than that. For example, population growth is often described as a logistic curve. It appears to be climbing exponentially initially, but then tapers off as resources can no longer support the population. [[Special:Contributions/108.162.246.191\|108.162.246.191]] 15:31, 8 November 2018 (UTC)
	:The explanation mentions the {{w\|logistic regression}} ranging between "0" and "1". It uses the more general {{w\|logistic function}} you probably refer to. The ''logistic regression'' uses in its basic form a ''logistic function'' to model a ''binary'' dependent variable. Both Wikipedia links explain the difference. Honestly, I'm not an expert on that matter but that binary interpretation wouldn't allow values above "1" or below "0" as shown in the picture. Maybe worth to be mentioned. Nonetheless all other fittings are also similar nonsense. Maybe we could mention the more general {{w\|Sigmoid function}} but this only barely fits to the title "Logistic Curve". --[[User:Dgbrt\|Dgbrt]] ([[User talk:Dgbrt\|talk]]) 23:09, 8 November 2018 (UTC)		:The explanation mentions the {{w\|logistic regression}} ranging between "0" and "1". It uses the more general {{w\|logistic function}} you probably refer to. The ''logistic regression'' uses in its basic form a ''logistic function'' to model a ''binary'' dependent variable. Both Wikipedia links explain the difference. Honestly, I'm not an expert on that matter but that binary interpretation wouldn't allow values above "1" or below "0" as shown in the picture. Maybe worth to be mentioned. Nonetheless all other fittings are also similar nonsense. Maybe we could mention the more general {{w\|Sigmoid function}} but this only barely fits to the title "Logistic Curve". --[[User:Dgbrt\|Dgbrt]] ([[User talk:Dgbrt\|talk]]) 23:09, 8 November 2018 (UTC)
		+
		+	Personally, I think the exponential fit seems like the most reasonable interpretation of the data.

← Older revision		Revision as of 23:09, 8 November 2018
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	The explanation for logistic curve currently says it is used for binary values. It's actually a lot more useful than that. For example, population growth is often described as a logistic curve. It appears to be climbing exponentially initially, but then tapers off as resources can no longer support the population. [[Special:Contributions/108.162.246.191\|108.162.246.191]] 15:31, 8 November 2018 (UTC)		The explanation for logistic curve currently says it is used for binary values. It's actually a lot more useful than that. For example, population growth is often described as a logistic curve. It appears to be climbing exponentially initially, but then tapers off as resources can no longer support the population. [[Special:Contributions/108.162.246.191\|108.162.246.191]] 15:31, 8 November 2018 (UTC)
		+	:The explanation mentions the {{w\|logistic regression}} ranging between "0" and "1". It uses the more general {{w\|logistic function}} you probably refer to. The ''logistic regression'' uses in its basic form a ''logistic function'' to model a ''binary'' dependent variable. Both Wikipedia links explain the difference. Honestly, I'm not an expert on that matter but that binary interpretation wouldn't allow values above "1" or below "0" as shown in the picture. Maybe worth to be mentioned. Nonetheless all other fittings are also similar nonsense. Maybe we could mention the more general {{w\|Sigmoid function}} but this only barely fits to the title "Logistic Curve". --[[User:Dgbrt\|Dgbrt]] ([[User talk:Dgbrt\|talk]]) 23:09, 8 November 2018 (UTC)

← Older revision		Revision as of 15:31, 8 November 2018
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	In both the '''logarithmic''' and '''exponential''' functions, I have deleted the term "+ ''c''" that was present in both. Simply put, these functions do not include an additive constant. To include the constant removes a basic property of e.g. exponential functions, which is that the function should grow by the same factor for equal increases in the value of ''x''. (In other words, if the functions doubles when ''x'' changes from 1 to 2, then it should double again when ''x'' changes from 2 to 3, or from 3 to 4, etc.) If this does not happen, the function is not exponential. [[User:Redbelly98\|Redbelly98]] ([[User talk:Redbelly98\|talk]]) 19:52, 13 October 2018 (UTC)		In both the '''logarithmic''' and '''exponential''' functions, I have deleted the term "+ ''c''" that was present in both. Simply put, these functions do not include an additive constant. To include the constant removes a basic property of e.g. exponential functions, which is that the function should grow by the same factor for equal increases in the value of ''x''. (In other words, if the functions doubles when ''x'' changes from 1 to 2, then it should double again when ''x'' changes from 2 to 3, or from 3 to 4, etc.) If this does not happen, the function is not exponential. [[User:Redbelly98\|Redbelly98]] ([[User talk:Redbelly98\|talk]]) 19:52, 13 October 2018 (UTC)
		+
		+
		+	'''Logistic Curve'''
		+
		+	The explanation for logistic curve currently says it is used for binary values. It's actually a lot more useful than that. For example, population growth is often described as a logistic curve. It appears to be climbing exponentially initially, but then tapers off as resources can no longer support the population. [[Special:Contributions/108.162.246.191\|108.162.246.191]] 15:31, 8 November 2018 (UTC)

← Older revision		Revision as of 19:52, 13 October 2018
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	Excel's "smooth lines" are actually splines ([https://blog.splitwise.com/2012/01/31/mystery-solved-the-secret-of-excel-curved-line-interpolation/ third-order Bezier splines, apparently]) so they're not completely without mathematical merit. Still wildly unsuited for extrapolation, but often very well suited to interpolation. [[User:JohnWhoIsNotABot\|JohnWhoIsNotABot]] ([[User talk:JohnWhoIsNotABot\|talk]]) 21:44, 24 September 2018 (UTC)		Excel's "smooth lines" are actually splines ([https://blog.splitwise.com/2012/01/31/mystery-solved-the-secret-of-excel-curved-line-interpolation/ third-order Bezier splines, apparently]) so they're not completely without mathematical merit. Still wildly unsuited for extrapolation, but often very well suited to interpolation. [[User:JohnWhoIsNotABot\|JohnWhoIsNotABot]] ([[User talk:JohnWhoIsNotABot\|talk]]) 21:44, 24 September 2018 (UTC)
		+
		+	'''Specific functions'''
		+
		+	In both the '''logarithmic''' and '''exponential''' functions, I have deleted the term "+ ''c''" that was present in both. Simply put, these functions do not include an additive constant. To include the constant removes a basic property of e.g. exponential functions, which is that the function should grow by the same factor for equal increases in the value of ''x''. (In other words, if the functions doubles when ''x'' changes from 1 to 2, then it should double again when ''x'' changes from 2 to 3, or from 3 to 4, etc.) If this does not happen, the function is not exponential. [[User:Redbelly98\|Redbelly98]] ([[User talk:Redbelly98\|talk]]) 19:52, 13 October 2018 (UTC)

← Older revision		Revision as of 21:44, 24 September 2018
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	Just want to note that the Piecewise models is actually a type of modelling often used in housing economics. It has been used to check if different types of housing are priced according to different rules. [[Special:Contributions/172.68.34.34\|172.68.34.34]] 22:05, 21 September 2018 (UTC)		Just want to note that the Piecewise models is actually a type of modelling often used in housing economics. It has been used to check if different types of housing are priced according to different rules. [[Special:Contributions/172.68.34.34\|172.68.34.34]] 22:05, 21 September 2018 (UTC)
		+
		+	Excel's "smooth lines" are actually splines ([https://blog.splitwise.com/2012/01/31/mystery-solved-the-secret-of-excel-curved-line-interpolation/ third-order Bezier splines, apparently]) so they're not completely without mathematical merit. Still wildly unsuited for extrapolation, but often very well suited to interpolation. [[User:JohnWhoIsNotABot\|JohnWhoIsNotABot]] ([[User talk:JohnWhoIsNotABot\|talk]]) 21:44, 24 September 2018 (UTC)

← Older revision		Revision as of 22:05, 21 September 2018
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	Anyways, what is the actual regression of the plot? {{unsigned ip\|162.158.154.241}}		Anyways, what is the actual regression of the plot? {{unsigned ip\|162.158.154.241}}
	:This also must be better explained: We don't know what the points represent. The fraction of apples vs. bananas harvested by time, the position of stars in the sky, on a logarithmic scale, linear, or maybe the height of mountains in New Jersey... There are just some dots on paper with no further meaning. Thus everything Randall presents is valid by some means but an actual regression does not exist. --[[User:Dgbrt\|Dgbrt]] ([[User talk:Dgbrt\|talk]]) 20:32, 21 September 2018 (UTC)		:This also must be better explained: We don't know what the points represent. The fraction of apples vs. bananas harvested by time, the position of stars in the sky, on a logarithmic scale, linear, or maybe the height of mountains in New Jersey... There are just some dots on paper with no further meaning. Thus everything Randall presents is valid by some means but an actual regression does not exist. --[[User:Dgbrt\|Dgbrt]] ([[User talk:Dgbrt\|talk]]) 20:32, 21 September 2018 (UTC)
		+
		+	Just want to note that the Piecewise models is actually a type of modelling often used in housing economics. It has been used to check if different types of housing are priced according to different rules. [[Special:Contributions/172.68.34.34\|172.68.34.34]] 22:05, 21 September 2018 (UTC)

@@ Line 42: / Line 42: @@
 I hate to be negative here, as obviously some users have put a lot of effort into explaining the details behind each of the curve-fitting methods, but there's absolutely no explanation for Randall's comments on each method.  While someone might learn something about the various methods by reading the explanation, they would not gain any insight on what Randall is saying about each method.  In addition, the Connecting Lines explanation totally missed the fact that this isn't really even a curve-fitting method - it's just a feature of graphing software (in this case, Excel) where a smooth line is drawn through each data point from left to right rather than an example of overfitting to the data set. I think we could do better. [[User:Ianrbibtitlht|Ianrbibtitlht]] ([[User talk:Ianrbibtitlht|talk]]) 02:53, 21 September 2018 (UTC)
 Everyone is missing the deeper trolling here of the fisheries community at large, which shall become blindingly clear here. First, this is cartoon number 2048 (2^11), a highly interesting number. Notably, this is the year all fisheries were projected to be collapsed by Worm et al. (2006) Science 314:787-790, a prediction which gained huge attention in the media and took on a life of its own. The prediction was based on fitting a power curve to some data on collapses in catch trends. Numerous rebuttals followed, one of which pointed out that a linear fit to the data is a better fit, and predicts all fisheries collapsed in 2114 (Jaenike et al. 2007, Science 316:1285a). A list of rebuttals is found here: https://sites.google.com/a/uw.edu/most-cited-fisheries/controversies/2048-projection. Later work by the same author and critics found a different prediction and showed rebuilding of fisheries is likely (Worm et al. 2009 Science 325:578-585). Second, lest you think this is a conspiracy theory, I note that in xkcd cartoon 887, Munroe specifically notes this prediction "The future according to google search results... 2048: "Salt-water fish extinct from overfishing" https://xkcd.com/887/. Third, this kind of model-fitting exercise has long plagued fisheries researchers attempting to predict recruitment from spawning biomass. {{unsigned ip|108.162.246.11}}
@@ Line 48: / Line 49: @@
 Anyways, what is the actual regression of the plot? {{unsigned ip|162.158.154.241}}