The tag has no wiki summary.

learn more… | top users | synonyms

7
votes
2answers
111 views

Selection of k knots in regression smoothing spline equivalent to k categorical variables?

I'm working on a predictive cost model where the patient's age (an integer quantity measured in years) is one of the predictor variables. A strong nonlinear relationship between age and risk of a ...
1
vote
1answer
23 views

R - How to smooth a conversion of weekly sales into daily sales?

I have weekly sales figures, and would like to convert them into daily sales figures, making a simple hypothesis that there are 7 days with equal sales "power". Let's imagine that I have: ...
1
vote
0answers
14 views

Line smoothness/waviness

I am working on a project which requires me to watch video of athletes and measure the straightness/smoothness/waviness, whatever term is acceptable, of their spine. Dividing the spine into segments ...
0
votes
0answers
19 views

How to generate a discrete 2D Gaussian smoothing kernel using R [migrated]

I'm wondering whether R has a function for this, or how to code, a 2D discrete version of a Gaussian smoothing kernel. The goal is to use this to smooth a 2D matrix of values.
2
votes
0answers
49 views

Modeling binary outcomes - inaccurate model when using logistic regression?

I am trying to model the probability of a binary outcome with the independent variable being an hour variable. I understand that linear regression is not the correct method for this type of task (I ...
6
votes
1answer
59 views

Kernel smoothing for Edgeworth expansion

Suppose I have an estimator which includes an indicator function in the objective function, then the objective function is not smooth. But if I want to approximate the behavior of this estimator in ...
0
votes
0answers
18 views

What is the difference between the metric window width and Nearest-neighbor's window in Kernel Smoothing methods?

I'm learning Kernel smoothing methods. I didn't really get the difference between the metric window width and Nearest-neighbor's window. For me both seem the same. Can anybody explain it to me? for ...
1
vote
0answers
25 views

How to set initial values for Holt-Winters backcasting?

I'm trying to figure out how to set initial seasonal values for backcasting of the multiplicative Holt Winters. As pointed out in this thread: Holt Winters initialization using backcasting like SPSS, ...
1
vote
0answers
40 views

smoothing nodes values on a graph given adjacency matrix

I am currently looking for a method to smooth values on a graph (composed of vertices and edges). For example I have a graph with a set of nodes V and I want to be able to smooth it. I could have ...
1
vote
1answer
88 views

What is a density function?

I know about histograms and also know that if we connect the mid-points on the top of bars in a histogram we will get a frequency polygon. This polygon could then be 'smoothed' in a way that it ...
5
votes
2answers
184 views

Laplace smoothing and Dirichlet prior

On the wikipedia article of Laplace smoothing (or additive smoothing), it is said that from a Bayesian point of view, this corresponds to the expected value of the posterior distribution, using a ...
0
votes
1answer
86 views

Using Moving-average smoothing in forecast package [closed]

I tried to use the non-centred moving average, that means just using past values by setting the option centre = FALSE, but unfortunately you get the centred results. Can anyone detect the failure ...
3
votes
0answers
163 views

confidence band around a smoothed function

I am using earth packageearth: Multivariate Adaptive Regression Spline Models regression to get a constant piecewise approximation of my data. I want to plot a band ...
1
vote
1answer
77 views

LOESS smoothing fit

Here are 3 questions about the LOESS smoothing fit. ...
0
votes
0answers
36 views

LOOCV for smoothing spline

The smoothing spline problem is $$ RSS(\theta,\lambda)=(y-N\theta)^T(y-N\theta)+\lambda\theta^T\Omega_N\theta $$ where $\{N\}_{ij}=N_j(x_i)$, $N_j(x)$ are an $N$-dimensional set of basis functions. ...
1
vote
2answers
75 views

Bayesian inference on possibly-non-linear effects

In my field, it is occasionally the case that we want to evaluate the degree to which some variable, Y, might be influenced by another variable, X, where X is measured across a range of continuous ...
1
vote
0answers
21 views

Data smoothing with derivative constraints

Which existing methods are capable of performing a smooth curve interpolation with constraints on derivative? What I need it to smooth my evenly spaced (with few missing points) data to get a smooth ...
3
votes
4answers
293 views

Finding inflection points in R from smoothed data

I have some data that I smooth using loess. I'd like to find the inflection points of the smoothed line. Is this possible? I'm sure someone has made a fancy method ...
0
votes
1answer
270 views

Formula that R “predict” function uses to calculate intervals exponential smoothing

I have been trying to figure out the exact formula that the R "predict" function uses to calculate prediction intervals for simple exponential smoothing. The prediction interval formula seems to vary ...
1
vote
2answers
122 views

How to explain smoothing functions in the logistic regression model

I fitted a logistic regression model with some smoothing functions, and the software made beautiful plots for them. Here is one example: My main concern is that there is no reference level in the ...
5
votes
2answers
237 views

How to smear a histogram

I was asked to perform a Gaussian smearing on the bins of an histogram. What does this mean?
5
votes
2answers
175 views

Variance of a smoothed AR(1) process

The query I have relates to calculating the variance of AR(1) processes that are smoothed with a simple moving average. So: In an AR(1) process of the form: $$ X_t=c+\varphi X_{t-1}+\varepsilon_t, ...
3
votes
2answers
81 views

What is smoothing in gaussian processes

I have been hearing this frequently that gaussian processes is a smoothing operation. I didn't get what they mean by that. Any clarifications guys?
1
vote
0answers
177 views

Holt Winters initialization using backcasting like SPSS

I'm trying to figure out how SPSS is initializing the multiplicative Holt Winters exponential smoothing model using backcasting. Thankfully IBM roughly described their way of doing so .. very roughly. ...
0
votes
1answer
257 views

Does the Holt-Winters algorithm for exponential smoothing in time series modelling require the normality assumption in residuals?

I'm working on a project to compare different approaches to time series modeling. In the model selection process, we perform residual analysis for the fitted models. For regression, we need to check ...
3
votes
0answers
108 views

Laplace smoothing parameter choice for Markov chain transitions

Let $Y_{t}$ be the state of the process at time $t$, ${\bf P}$ be the transition matrix then: $$ {\bf P}_{ij} = P(Y_{t} = j | Y_{t-1} = i) $$ Since this is a Markov chain, this probability depends ...
0
votes
2answers
113 views

Smoothing algorithm for saturating function

I have a noisy readout of a curve that is monotonically increasing or decreasing for a narrow range of points and then quickly saturates. I don't know exactly where the saturation point is, but from ...
1
vote
1answer
82 views

How to filter these extremely bad data points?

I'm looking at data for my company, and basically we have some periods over the last year where the data was not uploaded correctly. In this figure, "mu" is the value of interest, and duration is a ...
0
votes
1answer
91 views

How to quantify mis-specification bias and compare against smoothing bias for a non-parametric estimate of a randomly allocated continuous treatment?

Suppose that there is a data-generating process $$ y = \alpha + g(x) + \epsilon $$ which is to say that an outcome is some function of $x$. Suppose that $x$ is randomly assigned, so ...
0
votes
0answers
36 views

Curve smoothness - local adjacency

I am looking for statistical measures of curve smoothness. Time-series values {(1, 0.5), (4, -0.6), (200, 1.0)} where (time-unit, value) is linearly interpolated from one to the next. The smoothest ...
4
votes
2answers
185 views

Kernel density estimator that doesn't collapse in the tails

I have iid data-points $x_1, \dots, x_n$, generated by an unknown density $f(x)$. So far I have approximated $f(x)$ with a normal $N(\hat{\mu}, \hat{\sigma}^2 )$, where $\hat{\mu}$ and ...
3
votes
1answer
189 views

Mean squared error definition

I'm currently working through (part of) a textbook on non-parametric regression techniques. Regarding the choice of smoothing parameter the book starts out explaining the MSE which is defined as: ...
0
votes
0answers
41 views

Smoothing of log-distributed periodogram

I use the lomb-scargle periodogram to output information about chemical species in distinct time periods. This produces a distribution that is skewed heavily, with the majority of points and variance ...
1
vote
0answers
32 views

Differentiating experimental data

I'm trying to differentiate experimental data which are measured with time. However, the time increments are not equally spaced. I first obtained a trend line for these data and then did a linear ...
5
votes
2answers
216 views

Smoothing algorithm for irregular time interval

I have various sets of irregular interval time series data to which I want to apply some sort of smoothing algorithm to produce a good fit. I have attempted various methods which all were ...
1
vote
0answers
94 views

Is LOESS the appropriate way of visualizing my RT data?

I am conducting a Lexical Decision Task where my dependent random variable is Response Time (RT). My experimental design consists of 5 blocks of a 100 trials each. In each block, 50% of trials ...
0
votes
2answers
131 views

2d interpolation method for coarsely sampled image

I'm looking for a general method for 2d interpolation of a coarsely sampled image. I'll use an example, taken from the scipy.interpolate (Python) page. Say, I have this image, but instead of ...
4
votes
1answer
544 views

Rationale for the use of Regressogram (Bin-Smooth)

I am taking a class in data mining and we have recently been introduced to bin-smoothing in regression analysis but i cannot seem to understand the usefulness of this method nor how the method works ...
1
vote
0answers
38 views

Smoothing objective function

I have a current problem where i have a continuous error real function of n-variables, which is computationally expensive and (possibly) has multiple local minima (optima). I want to somehow smooth ...
2
votes
1answer
81 views

Computing lowess mean value

I am trying to reimplement the lowess algorithm in java. I read the matlab page explaining lowess with the following steps: Compute the regression weights for each data point in the span. A ...
1
vote
0answers
90 views

Computing weighted standard deviation using lowess mean values

I have two questions: First question: I want to compute the weighted standard deviation with tri-cubic kernel. I am using lowess function in R to compute the weighted mean using tri-cubic ...
7
votes
5answers
596 views

Smoothing 2D data

The data consist of optical spectra (light intensity against frequency) recorded at varying times. The points were acquired on a regular grid in x (time) , y (frequency). In order to analyse the time ...
1
vote
0answers
93 views

Automatically choose a bandwidth in R

I have a function that I have added noise to. I want to test a few smoothers, but for each smoother I want to minimise MSE. I know the underlying function, so how can I make R automatically choose the ...
1
vote
0answers
76 views

Good-Turing smoothing when everything appears once

I would like to use Good-Turing smoothing to find the probability of the next type of fish I will catch. If I have caught the following already: ...
4
votes
2answers
167 views

Smoothing a time series of ratios

I have a time series of proportions, $x_t = \frac{a_t}{b_t}$ i.e. $x_1 = 2 / 30, x_2 = 1/10$, ... I want to smooth $x_t$. Should I apply a smoothing function directly to $x_t$, or should I smooth ...
1
vote
1answer
483 views

Process for Standardising and Normalising data

First: I'm not well versed in statistics terminology so please forgive me - I'll try to be as verbose as possible with my problem. This is a problem which I've previously solved very naively. I'm ...
2
votes
0answers
133 views

Faster alternative to multivariate LOESS?

I want to make predictions by creating a smooth response surface to 2 variables. I get good results using R's loess() function, but with 10 million observations, it is far too slow. Are there any ...
2
votes
0answers
63 views

Smooth expectations outside the exponential family

At page 85-86 of Young and Smith "Essentials of Statistical Inference" there is an interesting result. If $X$ is a r.v. distributed according to the exponential family and $\phi(x)$ is a bounded (but ...
1
vote
0answers
387 views

optimal choice of smooth.spline parameter?

I'm analyzing a time series (terms of trades) on which I want to perform a trend estimation by nonparametric methods like the above mentioned. By the way, I'm a total beginner with R and using the ...
2
votes
0answers
82 views

local polynomial regression standard errors

I am attempting to find a reference which explains how one computes standard errors for local polynomial regression? Specifically, in R one can use the loess ...