1,725,820 research outputs found
jjackson-eco/timeline_demonstration: peer review 3
No full textThis directory contains scripts and analysis data for our work on an empirical demonstration of a sequence of signals preceding a population collapse in the ciliate _Paramecium caudatum_. For the manuscript please see [the Authorea entry](XXXX.XXXX.XXXX). Package version info for this analysis is given below.
Analysis scripts can be found in the `scripts/` sub-repository, figures in the `output/` sub-repository, and analysis data in the `data/` sub-repository.Scripts are labeled A and B in order of the analysis, and are as follows: 1. `A_data_cleaning.R` - Data cleaning, seasonal decomposition and supplementary figures. 2. `B_autocorrelation_k_selection.R` - Preparatory analysis selecting for k (basis dimension in GAM) and exploring autocorrelation 3. `C_gam_ews.R` - Additive model analysis for P.caudatum, include timeline component models and EWS analysis 4. `D_piecewise_regression.R`- Secondary analysis approach using piecewise Bayesian linear regression/Peer reviewe
Jackson, John, NX72749
No full textThis record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/394689Surname: JACKSON. Given Name(s) or Initials: JOHN. Military Service Number or Last Known Location: NX72749. Missing, Wounded and Prisoner of War Enquiry Card Index Number: 35803.218117
Item: [2016.0049.26982] "Jackson, John, NX72749
Les cadeaux de la grand'mère
No full textJackson John E. Les cadeaux de la grand'mère. In: Littératures 20, printemps 1989. pp. 63-71
The Rich Man and Lazarus (Lazzaro e il ricco Epulone)
No full textMedium: Chiaroscuro woodcutsigned."The Rich Man and Lazarus (Lazzaro e il ricco Epulone)" [1987.2037.000.000], Jackson, John Baptist, Bassano, JacopoArtist and Role: Jackson, John Baptist,Artist and Role: Bassano, Jacopo, ArtistExtent: Image 56.0 x 38.
Philippe Denis : l'insecte dans l'obscurité du bois
No full textJackson John E. Philippe Denis : l'insecte dans l'obscurité du bois. In: Littérature, n°110, 1998. pp. 81-87
Replication Data for: Corrected Standard Errors with Clustered Data
No full textThe use of cluster robust standard errors (CRSE) is commonas data are often collected from units, such as cities, states or countries, with multiple observations per unit. There is considerable discussion of how best to estimate standard errors and confidence intervals when using CRSE. Extensive simulations in this literature and here show that CRSE seriously underestimate coefficient standard errors and their associated confidence intervals, particularly with a small number of clusters and when there is little within cluster variation in the explanatory variables. These same simulations show that a method developed here provides more reliable estimates of coefficient standard errors. They underestimate confidence intervals for tests of individual and sets of coefficients in extreme conditions, but by far less than do CRSE. Simulations also show that this method produces more accurate standard error and confidence interval estimates than bootstrapping, which is often recommended as an alternative to CRSE
Replication Data for: Corrected Standard Errors with Clustered Data
No full textThe use of cluster robust standard errors (CRSE) is commonas data are often collected from units, such as cities, states or countries, with multiple observations per unit. There is considerable discussion of how best to estimate standard errors and confidence intervals when using CRSE. Extensive simulations in this literature and here show that CRSE seriously underestimate coefficient standard errors and their associated confidence intervals, particularly with a small number of clusters and when there is little within cluster variation in the explanatory variables. These same simulations show that a method developed here provides more reliable estimates of coefficient standard errors. They underestimate confidence intervals for tests of individual and sets of coefficients in extreme conditions, but by far less than do CRSE. Simulations also show that this method produces more accurate standard error and confidence interval estimates than bootstrapping, which is often recommended as an alternative to CRSE
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