Given a set of bivariate data (x, y), to impute a value of y corresponding to some value of x at which there is no measurement of y is called interpolation, if the value of x is within the range of the measured values of x.

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Inversely proportional version of a nearest-neighbour results vector - how?

Short version: Given an input vector D of n values, what are the different methods that one can use to return a vector W such that each value in W is in inverse proportion to the magnitudes of the ...
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13 views

Interpolating population data

I'm currently doing an internship where I have to calculate incidence ratios for townships for a period of 11 years. I don't have access to the population data for all years and I would like to do ...
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20 views

What is the correct way to interpolate error?

If I have a 2-D data, say $y = f(x)$, with error in the dependent variable, $\delta y$ in this case, and I want to interpolate this data set to a coarser independent variable grid, $x$, what is the ...
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21 views

gaussian process - missing data

One approach to deal with missing data is be to define a joint gaussian distribution / Gaussian process, and then define the (conditional) distribution of the unknown values on the known values. (e.g. ...
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1answer
113 views

Cubic splines for interpolation through four points in R

I am attempting to write R code for cubic splines to connect points on a graph. Specifically, I am attempting to reproduce Figure 3.3 of Wood (2006) ...
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34 views

How can we use genetic algorithm for curve fitting?

I want to use genetic algorithm in order to fit a curve to some data, or in other words, to estimate some equation that describes the relationship. Suppose that I select the equation to be a ...
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1answer
17 views

Interpolation model to estimate missing analytics

We have about 7 months of partially (30%) missing web analytics, that is apparently missing at random across all segmentations. We need to estimate the missing data to correctly compare current and ...
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1answer
51 views

How Does Kriging Interpolation work?

I am working on a problem in which I need to use Kriging to predict the value of some variables based on some surrounding variables. I want to implement its code by myself. So, I've went through too ...
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23 views

Interpreting margins of dummy variables [duplicate]

I have estimated an ordinal probit model in Stata. The dependent variable is walkability. The main independent variables are on a Likert scale (1=agree, 2=partially agree, 3=disagree). The other ...
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2answers
65 views

Which interpolation technique should I use?

I have an annual data set, but I have a few missing values in the series. I do not know which interpolation technique should I use to fill the missing values. ...
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2answers
44 views

Extrapolation of 2d movement

I have a problem with missing data in my dataset. My dataset is timeseries which contains x,y coordinates. I'd like to extrapolate missing values and use the assumption that I know speed and direction ...
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25 views

What issues may I face when interpolating my dependent variable in an OLS regression?

I'm doing my undergrad dissertation on what host-country factors impact FDI inflows - FDI inflows to the UK is my dependent variable. All of the independent variables I have managed to find at a ...
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20 views

creating polynomials using sets of data to represent a correlation

I need some guidance in creating a polynomial function that represents sets of data and its correlation, if that makes any sense. I know there Lagrange interpolation, least squares etc. I don't know ...
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23 views

Partition of function into pieces for interpolation needs

I've got some experimental data obtained from my mate's research. There are two sets of (x,y) points for each curve. He asked me to interpolate function values between these points, so for each curve ...
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47 views

Trend line for “discontinuous” data (missing data points)

How do I draw a trend line for data with missing points? There should be a measurement for each day, but sometimes the user forgets to take it. Here’s some data and my current approach: The data ...
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1answer
384 views

Normalize time series with different lengths with linear interpolation in R

I have a large set of time series (100k, each 3 observations), their lengths varies about 10% on average. Each of them cover the time interval of the same lengths but varies due to rate of sampling, ...
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0answers
13 views

Interpolating singular values

So I have the singular values associated with a data matrix and I would like to interpolate them and then find the maximum curvature of the interpolation in order to decide how many singular values to ...
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0answers
17 views

How to investigate higher frequency oscillation from lower frequency observations?

I have a set of data, e.g. chilled water flow rate, from a sensor reading, which record the value every half an hour. However, it yields irregular high-low pattern which bothers me quite much. Until ...
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37 views

Sampling subset to span entire range of full set (*not* to be representative), in order to construct some sort of lookup table

I have a large number of $N$ (20770) measurements. I need to perfom a calculation on all of them, but this is computationally too expensive. Therefore, I am looking for a way to select a subset of $p$ ...
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46 views

How to combine probabilities, weighting by strength of evidence?

Let's say that I'm trying to classify an item as a member of either class c1, class c2, class c3, etc. out of a large number of classes. In my training set, feature A appears only once; it happens to ...
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34 views

Is smooth.spline appropriate for presenting the trend of chemical concentration in a catchment [closed]

In my case,the Electrical Conductivity (EC) values are measured daily in some pints of catchment from 2007 to 2014, and around 20% data are missed, due to without probe or flux. To presenting the ...
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28 views

Imputing missing values of predictor for use in Regression Models

I have a panel data set that extends from January 2013 to July 2014. The response variable is complete for the entire period, however all of the predictor variables have values only up to June 2014. ...
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2answers
166 views

How to interpolate a variable with frequency of 5 years to annual data?

I have two time-series variables: each has 14 points with an interval of 5 years. The precise years are: ...
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77 views

What is the difference between Bézier splines and Loess curves?

I'm a bit naive on this topic, and wanted to understand the difference in the mechanics of Bézier splines and Loess curves as curve-fitting methods.
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1answer
112 views

In inverse theory, how do I transform the averaging kernel matrix to a new grid?

Rodgers and Connor (2003) describe how measurements by remote sounders can be properly compared, taking into account differences in averaging kernels and error covariances. They make the assumption ...
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2answers
108 views

Interpolating time series

what are best ways to interpolate time series? I have three data points(1980, 1990 and 2001) and I need to interpolate them. Using R na.approx doesn't seem to be what I need since the data I need to ...
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23 views

Predicting the missing data out of three values in each of the two vectors [duplicate]

I have 2 vectors of rural and urban populations of the same country. (years from 1975 to 2020) with only three values (1980, 1990 and 2001 years) in each. And I need to predict the missing data. My ...
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1answer
254 views

How to interpolate (spline, LOESS, etc.) with a mix of critical and non-critical points

The data we are interpolating is monotonically increasing (for example, a car's odometer reading). We have two types of points we'd like the solution to interpolate through. The solution surface must ...
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1answer
282 views

What is the difference between (universal) kriging and spatial autoregressive models?

As part of a course on missing observations in social/survey statistics I am trying to explore existing methods of predicting either point pattern or polygon data. I got quite confused by all the ...
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1answer
47 views

Multivariate interpolation: Getting Started

I have a large set of data points received by experimentation and each point has n ,or let's say 8 in this case, independent variables and one output/dependent variable. (x1, x2, x3, ...., xn) = y ...
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163 views

SUTSE DLM on daily mean water & air temperature TS

I have two time series: (1) daily mean water temperature from 1988 to 2014 and (2) daily mean air temperature from 1968 to 2010. The water temperature time series has missing data, occurring on ...
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192 views

Interpolating time series wind data using correlation

Is there a way to use correlation to interpolate missing data? I know the wind speed in 6 locations every hour. This shows the correlation between the separate locations. Hourly Data I know the wind ...
3
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1answer
63 views

How can I estimate the tail of a distribution with a truncated distribution?

The broadband speed data I'm working with have all values over 30Mbps placed into a >30 category. The distribution is thus truncated. This leads to the final column in the histogram below being a ...
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87 views

How to enforce periodic boundary conditions when performing regression with sci-kit learn?

I have signals that resemble sine waves (or, more accurately, sums of sines). The data are normalized in the time domain so that there is only one cycle and all of the points lie between 0 and 1. An ...
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1answer
173 views

Denormalizing Data

I am applying Polynomial Regression to my data, however the parameters theta were always =0, i noticed that my y data or output is too large in the order of 100000 so i normalized y, i got very good ...
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1answer
297 views

How to interpolate independent variable over five-year period?

I have panel data on income and population for the years 1990, 1995, 2000 and 2005. I would like to interpolate these two variables (both independent variables), so that I have data for every year ...
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0answers
50 views

Interpolation of time series data

I am working on using cubic spline interpolation in time series data. I used Galdolfo and Prachowney algorithms. Now how do I obtain estimates of models of cubic spline?
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1answer
50 views

How to take into consideration gaps in time series?

I've been analysing what is the probability of that measurement going up or down during a week (e.g. 4 times out of 7, I have 60% chances of my measurement going up) everyday for the last 100 days, ...
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43 views

Limitations of using interpolated data

I have a data set that is composed of point locations in a landscape, lets call this dataset X. Some of the points in data set X need to be grouped together because they "function" together as a ...
3
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1answer
421 views

Find out if there is a way to create BMI weight category variable

I am working on a project and have to find a way to break my data into percentiles. The variables that I already have are gender, age in months and BMI. If I am able to calculate the percentile that ...
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105 views

How to select a radial basis function?

Currently I am investigating interpolation of 3D data with radial basis functions (RBF) and I am wondering that there are quite a few families of such (see table1 here). However, I cannot find any ...
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1answer
221 views

Explanation of cubic spline interpolation

Can someone explain to me what a cubic spline is, and how we could use it to interpolate a function? I have searched on the internet but I would like a simple explanation.
3
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1answer
192 views

Kriging without covariance?

I am trying to krige monthly snowfall totals using data from weather stations and elevation. When I use a linear variogram model (set using a GUI and appears to be a good fit), the resulting layer ...
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0answers
70 views

Interpolation problem [closed]

We have the following solar meteorology parameters through satellite data with resolution of 100 km$^2$ (10 km x 10 km). Insolation on horizontal surface Diffuse radiation on horizontal ...
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1answer
113 views

How to algorithmically determine the best order of fit?

I am doing a least squares polynomial interpolation for 10,000 data sets that look mostly like one period of a sine curve, but whose values are not evenly spaced in the time domain, and can sometimes ...
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0answers
47 views

Dimension independent regression/interpolation methods?

Hopefully this question is not too simple or too general. I am working on a problem right now in which I am given different sets of data. Each data set consists of some number of samples (sampled at ...
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0answers
85 views

Appropriate algorithms for interpolating 2D plane

I have a dataset describing a signal on a 2D plane. The data can be spaced at arbitrary increments. If it was an ordered grid, I understand bicubic interpolation would be a good choice. In the ...
5
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1answer
765 views

Uncertainty propagation in linear interpolation

How do I calculate the uncertainties in linearly interpolated values from a given tabulated function? I am just coming back into the fold after a bit of a hiatus, and am having trouble ...
3
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1answer
71 views

Interpolation of spectra: uneven sampling to even sampling

I have a spectrum. Specifically, my data is relative intensity $[I_{\tilde{\nu}}]$ versus wavenumbers $[\tilde{\nu}]$. The wavenumbers are equally sampled so that ${d\tilde{\nu}} = c$, where $c$ is ...
15
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1answer
6k views

How do I find values not given in (interpolate in) statistical tables?

Often people use programs to obtain p-values, but sometimes - for whatever reason - it may be necessary to obtain a critical value from a set of tables. Given a statistical table with a limited ...