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  • Exponential regression : p-value and F significance

    - by Saravanan K
    I am new to statistics. I have a set of independent data and dependent data (X,Y), where I would like to do an exponential regression to obtain its p-value and significant F (already obtained R2 and also the coefficients through mathematical calculation). What is the natural evolution from the (X,Y) data to mathematically calculate those variables. Spent a week on the internet to study this but unable to find the right answer. Often an exponential data, y=be^(mx) will be converted first to a linear data, ln y = mx + ln b . Then a linear regression will done on the converted data, obtaining its p-value etc. Assume we use a statistical tool such as Excel's Analysis ToolPak: Data Analysis : Regression, it will produce a result such as below, I believe the p-value and Significant F value is representing the converted linear data and not the original exponential data. Questions: What is the approach/steps used by Excel to get the p-value and Significant F value for the converted linear data as shown in the statistic output in the image above? It is not clear in their help page or website. Can the p-value and Significant F could be mathematically calculated for exponential regression without using a statistical tool? Can you assist to point me to the right link if this has been answered before.

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  • Using exponential smoothing with NaN values

    - by Eric
    I have a sample of some kind that can create somewhat noisy output. The sample is the result of some image processing from a camera, which indicates the heading of a blob of a certain color. It is an angle from around -45° to +45°, or a NaN, which means that the blob is not actually in view. In order to combat the noisy data, I felt that exponential smoothing would do the trick. However, I'm not sure how to handle the NaN values. On the one hand, involving them in the math would result in a NaN average, which would then prevent any meaningful results. On the other hand, ignoring NaN values completely would mean that a "no-detection" scenario would never be reported. And just to complicate things, the data is also noisy in that it can get false NaN value, which ideally would be smoothed somehow to prevent random noise. Any ideas about how I could implement such an exponential smoother?

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  • Exponential volume control with a specified midpoint

    - by Lars
    I have a slider that returns values from 0 to 100. I am using this to control the gain of an oscillator. When the slider is at 0, I would like the gain to be 0.0 When the slider is at 50, I would like the gain to be 0.1 When the slider is at 100, I would like the gain to be 0.5 So I need to find an equation to get a smooth curve which passes through all of these points. I've got the following equation which gives an exponential curve and gets the start and end points correct, but I don't know how to force the curve through the middle point. Can anyone help? function logSlider(position){ var minP = 0; var maxP = 100; var minV = Math.log(0.0001); var maxV = Math.log(0.5); var scale = (maxV - minV) / (maxP - minP); return Math.exp(minV + scale*(position-minP)); }

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  • Python fit polynomial, power law and exponential from data

    - by Nadir
    I have some data (x and y coordinates) coming from a study and I have to plot them and to find the best curve that fits data. My curves are: polynomial up to 6th degree; power law; and exponential. I am able to find the best fit for polynomial with while(i < 6): coefs, val = poly.polyfit(x, y, i, full=True) and I take the degree that minimizes val. When I have to fit a power law (the most probable in my study), I do not know how to do it correctly. This is what I have done. I have applied the log function to all x and y and I have tried to fit it with a linear polynomial. If the error (val) is lower than the others polynomial tried before, I have chosen the power law function. Am I correct? Now how can I reconstruct my power law starting from the line y = mx + q in order to draw it with the original points? I need also to display the function found. I have tried with: def power_law(x, m, q): return q * (x**m) using x_new = np.linspace(x[0], x[-1], num=len(x)*10) y1 = power_law(x_new, coefs[0], coefs[1]) popt, pcov = curve_fit(power_law, x_new, y1) but it seems not to work well.

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  • Oracle Database 11g Helps Control Exponential Data Growth

    - by [email protected]
    The 2010 ESG annual customer survey is now available. As part of it, ESG interviewed 300 customers about their IT priorities and, unsurprisingly, "Manage Data Growth" is top of the list. Perhaps less self-evident is the proposed solution to target this prime concern: "Often overlooked because it is a database platform, Oracle Database 11g offers additional capabilities such as automatic storage management (ASM), advanced data compression, and data protection that make managing data growth much easier for organizations of any size." The paper goes on to discuss these capabilities and highlights their potential benefits. Oracle Database 11g Helps Control Exponential Database Growth - a worthwhile read for anyone having to deal with rapidly increasing amounts of data. Download your free copy here.

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  • Is incrementing in a loop exponential time?

    - by user356106
    I've a simple but confusing doubt about whether the program below runs in exponential time. The question is : given a +ve integer as input, print it out. The catch is that you deliberately do this in a loop, like this: int input,output=0; cininput; while(input--) ++output; // Takes time proportional to the value of input cout<< output; I'm claiming that this problem runs in exponential time. Because, the moment you increase the # of bits in input by 1, the program takes double the amount of time to execute. Put another way, to print out log2(input) bits, it takes O(input) time. Is this reasoning right?

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  • Optimizing division/exponential calculation

    - by Saltheart
    I've inherited a Visual Studio/VB.Net numerical simulation project that has a likely inefficient calculation. Profiling indicates that the function is called a lot (1 million times plus) and spends about 50% of the overall calculation within this function. Here is the problematic portion Result = (A * (E ^ C)) / (D ^ C * B) (where A-C are local double variables and D & E global double variables) Result is then compared to a threshold which might have additional improvements as well, but I'll leave them another day any thoughts or help would be appreciated Steve

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  • Problem in displaying numbers in Flex AdvancedDataGrid

    - by user211607
    Hi, I am able to display any data (numbers) in Flex AdvancedDataGrid except data with lot of digits after decimal places (0.000000000029103830456733704) or exponential numbers (293E-17). Grid is displaying -17 instead of 293E-17. Is it happening because of any limit to displaying data range in grid? If yes, what is the limit? Thanks in advance ... Atul

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  • Computing e^(-j) in C..

    - by Erkan H
    I need to compute imaginary exponential in C. As far as I know, there is no complex number library in C. It is possible to get e^x with exp(x) of math.h, but how can I compute the value of e^(-j), where j = sqrt(-1)?

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  • Modifying multiplying calculation to use delta time

    - by Bart van Heukelom
    function(deltaTime) { x = x * 0.9; } This function is called in a game loop. First assume that it's running at a constant 30 FPS, so deltaTime is always 1/30. Now the game is changed so deltaTime isn't always 1/30 but becomes variable. How can I incorporate deltaTime in the calculation of x to keep the "effect per second" the same?

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  • C: Random Number Generation - What (If Anything) Is Wrong With This

    - by raoulcousins
    For a simple simulation in C, I need to generate exponential random variables. I remember reading somewhere (but I can't find it now, and I don't remember why) that using the rand() function to generate random integers in a fixed range would generate non-uniformly distributed integers. Because of this, I'm wondering if this code might have a similar problem: //generate u ~ U[0,1] u = ( (double)rand() / ((double)(RAND_MAX)); //inverse of exponential CDF to get exponential random variable expon = -log(1-u) * mean; Thank you!

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  • Is there an exponent operator in C#?

    - by Charlie
    For example, does an operator exist to handle this? float Result, Number1, Number2; Number1 = 2; Number2 = 2; Result = Number1 (operator) Number2; In the past the ^ operator has served as an exponential operator in other languages, but in C# it is a bit-wise operator. Do I have to write a loop or include another namespace to handle exponential operations? If so, how do I handle exponential operations using non-integers?

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  • Time Complexities of recursive algorithms

    - by Peter
    Whenever I see a recursive solution, or I write recursive code for a problem, it is really difficult for me to figure out the time complexity, in most of the cases I just say its exponential? How is it exponential actually? How people say it is 2^n, when it is n!, when it is n^n or n^k. I have some questions in mind, let say find all permutations of a string (O(n!)) find all sequences which sum up to k in an array (exponential, how exactly do I calculate). Find all subsets of size k whose sum is 0 (will k come somewhere in complexity , it should come right?). Can any1 help me how to calculate the exact complexity of such questions, I am able to wrote code for them , but its hard understanding the exact time complexity.

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  • Import exponetial fixed width format data into Excel

    - by Tom Daniel
    I've received a bunch of text data files consiting of Lots of records (30K/file) of 3 fields each of 5-place numbers in exponential format: s0.nnnnnEsee (where s is +/-, n is a digit and ee is the exponent (always 2 digit). When I open the file in Notepad, the format is perfectly uniform throughout each file, but when I import it to Excel using Data|Import|Fixed Width, many of the data values get messed up, no matter what format (text, exponential, various custom tries) I assign to the cells. Looking at the Notepad version, it appears that leading + signs were replaced with a space in the data file, but the sign of the exponential is always there. This means that some fields begin with a space, and this appears to confuse the Excel import routine. I get the same result in Excel 2003 and 2007. I'm sure there's a straightforward solution (hopefully without a messy VBA routine), but I can't figure out what to try next. :-) To clarify (hopefully), here are some input records and the corresponding text input to Excel: Notepad Excel -0.11311E+01 0.10431E-04 0.27018E-03 -0.11311E 1.0431E-05 2.7018E-04 0.19608E+00-0.81414E-02-0.89553E-02 0.19608E -8.1414E-03 8.9553E-03 etc. Whoopee! Solved my own problem - in the spirit of Jeopardy, now that I've begun the question, here's the answer - Use a different "File Origin" - several other than the default "Unicode UTF..." work fine! What a pain. Hope this helps somebody else avoid a few unpleasant hours! Aloha from Kona, Tom

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  • Adding more than 15 digits in excel

    - by user111921
    I want to add more than 20 digits in an Excel cell. The current format of the cell is general, it converts the number to an exponential format. I tried with a number format and accounting but when I enter more than 15 digits it gets converted to 0's. Please recommend steps for stopping Excel from converting data to Exponential Format for 20 digits when in the general format. Example: 12345678901234567890 Excel converts it to 1.23457E+19 in general format. with out using ' before value is there any other way to keep value same.

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  • Extreme Optimization –Mathematical Constants and Basic Functions

    - by JoshReuben
    Machine constants The MachineConstants class - contains constants for floating-point arithmetic because the CLS System.Single and Double floating-point types do not follow the standard conventions and are useless. machine constants for the Double type: machine precision: Epsilon , SqrtEpsilon CubeRootEpsilon largest possible value: MaxDouble , SqrtMaxDouble, LogMaxDouble smallest Double-precision floating point number that is greater than zero: MinDouble , SqrtMinDouble , LogMinDouble A similar set of constants is available for the Single Datatype  Mathematical Constants The Constants class contains static fields for many mathematical constants and common expressions involving small integers – if you are doing thousands of iterations, you wouldn't want to calculate OneOverSqrtTwoPi , Sqrt17 or Log17 !!! Fundamental constants E - The base for the natural logarithm, e (2.718...). EulersConstant - (0.577...). GoldenRatio - (1.618...). Pi - the ratio between the circumference and the diameter of a circle (3.1415...). Expressions involving fundamental constants: TwoPi, PiOverTwo, PiOverFour, LogTwoPi, PiSquared, SqrPi, SqrtTwoPi, OneOverSqrtPi, OneOverSqrtTwoPi Square roots of small integers: Sqrt2, Sqrt3, Sqrt5, Sqrt7, Sqrt17 Logarithms of small integers: Log2, Log3, Log10, Log17, InvLog10  Elementary Functions The IterativeAlgorithm<T> class in the Extreme.Mathematics namespace defines many elementary functions that are missing from System.Math. Hyperbolic Trig Functions: Cosh, Coth, Csch, Sinh, Sech, Tanh Inverse Hyperbolic Trig Functions: Acosh, Acoth, Acsch, Asinh, Asech, Atanh Exponential, Logarithmic and Miscellaneous Functions: ExpMinus1 - The exponential function minus one, ex-1. Hypot - The hypotenuse of a right-angled triangle with specified sides. LambertW - Lambert's W function, the (real) solution W of x=WeW. Log1PlusX - The natural logarithm of 1+x. Pow - A number raised to an integer power.

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  • SQL SERVER – Fix : Error 3623 – An invalid floating point operation occurred

    - by pinaldave
    Going back in time, I always had a problem with mathematics. It was a great subject and I loved it a lot but I only mastered it after practices a lot. I learned that mathematics problems should be addressed systematically and being verbose is not a trick, I learned to solve any problem. Recently one of reader sent me an email with the title “Mathematics problem – please help!” and I was a bit scared. I was good at mathematics but not the best. When I opened the email I was relieved as it was Mathematics problem with SQL Server. My friend received following error while working with SQL Server. Msg 3623, Level 16, State 1, Line 1 An invalid floating point operation occurred. The reasons for the error is simply that invalid usage of the mathematical function is attempted. Let me give you a few examples of the same. SELECT SQRT(-5); SELECT ACOS(-3); SELECT LOG(-9); If you run any of the above functions they will give you an error related to invalid floating point. Honestly there is no workaround except passing the function appropriate values. SQRT of a negative number will give you result in real numbers which is not supported at this point of time as well LOG of a negative number is not possible (because logarithm is the inverse function of an exponential function and the exponential function is NEVER negative). When I send above reply to my friend he did understand that he was passing incorrect value to the function. As mentioned earlier the only way to fix this issue is finding incorrect value and avoid passing it to the function. Every mathematics function is different and there is not a single solution to identify erroneous value passed. If you are facing this error and not able to figure out the solution. Post a comment and I will do my best to figure out the solution. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Error Messages, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • What Precalculus knowledge is required before learning Discrete Math Computer Science topics?

    - by Ein Doofus
    Below I've listed the chapters from a Precalculus book as well as the author recommended Computer Science chapters from a Discrete Mathematics book. Although these chapters are from two specific books on these subjects I believe the topics are generally the same between any Precalc or Discrete Math book. What Precalculus topics should one know before starting these Discrete Math Computer Science topics?: Discrete Mathematics CS Chapters 1.1 Propositional Logic 1.2 Propositional Equivalences 1.3 Predicates and Quantifiers 1.4 Nested Quantifiers 1.5 Rules of Inference 1.6 Introduction to Proofs 1.7 Proof Methods and Strategy 2.1 Sets 2.2 Set Operations 2.3 Functions 2.4 Sequences and Summations 3.1 Algorithms 3.2 The Growths of Functions 3.3 Complexity of Algorithms 3.4 The Integers and Division 3.5 Primes and Greatest Common Divisors 3.6 Integers and Algorithms 3.8 Matrices 4.1 Mathematical Induction 4.2 Strong Induction and Well-Ordering 4.3 Recursive Definitions and Structural Induction 4.4 Recursive Algorithms 4.5 Program Correctness 5.1 The Basics of Counting 5.2 The Pigeonhole Principle 5.3 Permutations and Combinations 5.6 Generating Permutations and Combinations 6.1 An Introduction to Discrete Probability 6.4 Expected Value and Variance 7.1 Recurrence Relations 7.3 Divide-and-Conquer Algorithms and Recurrence Relations 7.5 Inclusion-Exclusion 8.1 Relations and Their Properties 8.2 n-ary Relations and Their Applications 8.3 Representing Relations 8.5 Equivalence Relations 9.1 Graphs and Graph Models 9.2 Graph Terminology and Special Types of Graphs 9.3 Representing Graphs and Graph Isomorphism 9.4 Connectivity 9.5 Euler and Hamilton Ptahs 10.1 Introduction to Trees 10.2 Application of Trees 10.3 Tree Traversal 11.1 Boolean Functions 11.2 Representing Boolean Functions 11.3 Logic Gates 11.4 Minimization of Circuits 12.1 Language and Grammars 12.2 Finite-State Machines with Output 12.3 Finite-State Machines with No Output 12.4 Language Recognition 12.5 Turing Machines Precalculus Chapters R.1 The Real-Number System R.2 Integer Exponents, Scientific Notation, and Order of Operations R.3 Addition, Subtraction, and Multiplication of Polynomials R.4 Factoring R.5 Rational Expressions R.6 Radical Notation and Rational Exponents R.7 The Basics of Equation Solving 1.1 Functions, Graphs, Graphers 1.2 Linear Functions, Slope, and Applications 1.3 Modeling: Data Analysis, Curve Fitting, and Linear Regression 1.4 More on Functions 1.5 Symmetry and Transformations 1.6 Variation and Applications 1.7 Distance, Midpoints, and Circles 2.1 Zeros of Linear Functions and Models 2.2 The Complex Numbers 2.3 Zeros of Quadratic Functions and Models 2.4 Analyzing Graphs of Quadratic Functions 2.5 Modeling: Data Analysis, Curve Fitting, and Quadratic Regression 2.6 Zeros and More Equation Solving 2.7 Solving Inequalities 3.1 Polynomial Functions and Modeling 3.2 Polynomial Division; The Remainder and Factor Theorems 3.3 Theorems about Zeros of Polynomial Functions 3.4 Rational Functions 3.5 Polynomial and Rational Inequalities 4.1 Composite and Inverse Functions 4.2 Exponential Functions and Graphs 4.3 Logarithmic Functions and Graphs 4.4 Properties of Logarithmic Functions 4.5 Solving Exponential and Logarithmic Equations 4.6 Applications and Models: Growth and Decay 5.1 Systems of Equations in Two Variables 5.2 System of Equations in Three Variables 5.3 Matrices and Systems of Equations 5.4 Matrix Operations 5.5 Inverses of Matrices 5.6 System of Inequalities and Linear Programming 5.7 Partial Fractions 6.1 The Parabola 6.2 The Circle and Ellipse 6.3 The Hyperbola 6.4 Nonlinear Systems of Equations

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  • Oracle Fusion Middleware on YouTube

    - by Michelle Kimihira
    Now, you can watch Fusion Middleware videos on YouTube (Channel = OracleFusionMiddle). Today, we are featuring 2 customer interviews with Amit Zavery, VP of Product Management, Oracle Fusion Middleware: UL achives exponential growth using Oracle Engineered Systems Boeing transforms their supply chain process using Oracle Business Process Management Check it out today! Additional Information Product Information on Oracle.com: Oracle Fusion Middleware Follow us on Twitter and Facebook Subscribe to our regular Fusion Middleware Newsletter

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  • Worse is better. Is there an example?

    - by J.F. Sebastian
    Is there a widely-used algorithm that has time complexity worse than that of another known algorithm but it is a better choice in all practical situations (worse complexity but better otherwise)? An acceptable answer might be in a form: There are algorithms A and B that have O(N**2) and O(N) time complexity correspondingly, but B has such a big constant that it has no advantages over A for inputs less then a number of atoms in the Universe. Examples highlights from the answers: Simplex algorithm -- worst-case is exponential time -- vs. known polynomial-time algorithms for convex optimization problems. A naive median of medians algorithm -- worst-case O(N**2) vs. known O(N) algorithm. Backtracking regex engines -- worst-case exponential vs. O(N) Thompson NFA -based engines. All these examples exploit worst-case vs. average scenarios. Are there examples that do not rely on the difference between the worst case vs. average case scenario? Related: The Rise of ``Worse is Better''. (For the purpose of this question the "Worse is Better" phrase is used in a narrower (namely -- algorithmic time-complexity) sense than in the article) Python's Design Philosophy: The ABC group strived for perfection. For example, they used tree-based data structure algorithms that were proven to be optimal for asymptotically large collections (but were not so great for small collections). This example would be the answer if there were no computers capable of storing these large collections (in other words large is not large enough in this case). Coppersmith–Winograd algorithm for square matrix multiplication is a good example (it is the fastest (2008) but it is inferior to worse algorithms). Any others? From the wikipedia article: "It is not used in practice because it only provides an advantage for matrices so large that they cannot be processed by modern hardware (Robinson 2005)."

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  • How meaningful is the Big-O time complexity of an algorithm?

    - by james creasy
    Programmers often talk about the time complexity of an algorithm, e.g. O(log n) or O(n^2). Time complexity classifications are made as the input size goes to infinity, but ironically infinite input size in computation is not used. Put another way, the classification of an algorithm is based on a situation that algorithm will never be in: where n = infinity. Also, consider that a polynomial time algorithm where the exponent is huge is just as useless as an exponential time algorithm with tiny base (e.g., 1.00000001^n) is useful. Given this, how much can I rely on the Big-O time complexity to advise choice of an algorithm?

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  • Gumblar Attack

    Gumblar appears to be a combination of exploit scripts and malware. The scripts are embedded in .html, .js and .php files using obfuscated Javascript. They load malware content from Third Party sites without the user’s knowledge, while also stealing FTP credentials from the victim’s computer, which then allows it to spread and infect additional sites. Therefore, when someone visits such an infected site they get infected; if they have FTP credentials for a website on their machine then those sites get infected too. This explains the exponential growth of the exploit in such a short space of time.

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  • How to increase ad revenue

    - by Brian515
    I have an Android game in which I've included ads from Millennial Media and Admob. Between these two networks, my fill rate is consistently above 95%. Right now, I'm getting over 45,000 requests for ads per day, and I'm starting to see exponential growth. But, my eCpm for both Millennial and Admob is ridiculously low. Millennial's is $.12 and Admob's is $.01. I've been reading some other posts and it seems like people are getting between $1 and $4 per 1,000 views. How can increase mine? Thank you!

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